Overview

Dataset statistics

Number of variables62
Number of observations74
Missing cells1853
Missing cells (%)40.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory36.0 KiB
Average record size in memory497.7 B

Variable types

Numeric11
Categorical42
Unsupported9

Alerts

type has constant value "regular" Constant
airdate has constant value "2020-12-29" Constant
_embedded.show.externals.tvrage has constant value "19056.0" Constant
_embedded.show.dvdCountry.name has constant value "Ukraine" Constant
_embedded.show.dvdCountry.code has constant value "UA" Constant
_embedded.show.dvdCountry.timezone has constant value "Europe/Zaporozhye" Constant
url has a high cardinality: 74 distinct values High cardinality
name has a high cardinality: 61 distinct values High cardinality
_links.self.href has a high cardinality: 74 distinct values High cardinality
id is highly correlated with rating.average and 2 other fieldsHigh correlation
season is highly correlated with rating.average and 2 other fieldsHigh correlation
number is highly correlated with rating.average and 3 other fieldsHigh correlation
runtime is highly correlated with rating.average and 3 other fieldsHigh correlation
rating.average is highly correlated with id and 9 other fieldsHigh correlation
_embedded.show.id is highly correlated with rating.average and 3 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with runtime and 2 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with runtime and 4 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with id and 7 other fieldsHigh correlation
_embedded.show.weight is highly correlated with rating.average and 3 other fieldsHigh correlation
_embedded.show.webChannel.id is highly correlated with rating.average and 2 other fieldsHigh correlation
_embedded.show.externals.thetvdb is highly correlated with season and 6 other fieldsHigh correlation
_embedded.show.updated is highly correlated with rating.average and 3 other fieldsHigh correlation
_embedded.show.network.id is highly correlated with id and 9 other fieldsHigh correlation
id is highly correlated with rating.average and 2 other fieldsHigh correlation
season is highly correlated with number and 5 other fieldsHigh correlation
number is highly correlated with season and 6 other fieldsHigh correlation
runtime is highly correlated with number and 4 other fieldsHigh correlation
rating.average is highly correlated with id and 9 other fieldsHigh correlation
_embedded.show.id is highly correlated with season and 5 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with season and 3 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with runtime and 4 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with id and 7 other fieldsHigh correlation
_embedded.show.weight is highly correlated with rating.average and 2 other fieldsHigh correlation
_embedded.show.webChannel.id is highly correlated with rating.average and 2 other fieldsHigh correlation
_embedded.show.externals.thetvdb is highly correlated with season and 4 other fieldsHigh correlation
_embedded.show.updated is highly correlated with rating.average and 2 other fieldsHigh correlation
_embedded.show.network.id is highly correlated with id and 9 other fieldsHigh correlation
id is highly correlated with rating.average and 2 other fieldsHigh correlation
season is highly correlated with rating.average and 2 other fieldsHigh correlation
number is highly correlated with rating.average and 2 other fieldsHigh correlation
runtime is highly correlated with rating.average and 3 other fieldsHigh correlation
rating.average is highly correlated with id and 9 other fieldsHigh correlation
_embedded.show.id is highly correlated with rating.average and 2 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with runtime and 2 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with runtime and 4 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with id and 7 other fieldsHigh correlation
_embedded.show.weight is highly correlated with rating.average and 2 other fieldsHigh correlation
_embedded.show.webChannel.id is highly correlated with rating.average and 2 other fieldsHigh correlation
_embedded.show.externals.thetvdb is highly correlated with season and 4 other fieldsHigh correlation
_embedded.show.updated is highly correlated with rating.average and 2 other fieldsHigh correlation
_embedded.show.network.id is highly correlated with id and 7 other fieldsHigh correlation
id is highly correlated with url and 37 other fieldsHigh correlation
url is highly correlated with id and 43 other fieldsHigh correlation
name is highly correlated with id and 25 other fieldsHigh correlation
season is highly correlated with url and 25 other fieldsHigh correlation
number is highly correlated with url and 31 other fieldsHigh correlation
airtime is highly correlated with id and 36 other fieldsHigh correlation
airstamp is highly correlated with id and 39 other fieldsHigh correlation
runtime is highly correlated with id and 40 other fieldsHigh correlation
summary is highly correlated with id and 36 other fieldsHigh correlation
_links.self.href is highly correlated with id and 43 other fieldsHigh correlation
_embedded.show.id is highly correlated with id and 28 other fieldsHigh correlation
_embedded.show.url is highly correlated with id and 42 other fieldsHigh correlation
_embedded.show.name is highly correlated with id and 42 other fieldsHigh correlation
_embedded.show.type is highly correlated with id and 41 other fieldsHigh correlation
_embedded.show.language is highly correlated with id and 40 other fieldsHigh correlation
_embedded.show.status is highly correlated with url and 37 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with id and 43 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with id and 40 other fieldsHigh correlation
_embedded.show.premiered is highly correlated with id and 42 other fieldsHigh correlation
_embedded.show.ended is highly correlated with id and 33 other fieldsHigh correlation
_embedded.show.officialSite is highly correlated with id and 42 other fieldsHigh correlation
_embedded.show.schedule.time is highly correlated with url and 36 other fieldsHigh correlation
_embedded.show.weight is highly correlated with url and 35 other fieldsHigh correlation
_embedded.show.webChannel.id is highly correlated with id and 32 other fieldsHigh correlation
_embedded.show.webChannel.name is highly correlated with id and 35 other fieldsHigh correlation
_embedded.show.webChannel.officialSite is highly correlated with id and 34 other fieldsHigh correlation
_embedded.show.externals.thetvdb is highly correlated with url and 24 other fieldsHigh correlation
_embedded.show.externals.imdb is highly correlated with id and 38 other fieldsHigh correlation
_embedded.show.image.medium is highly correlated with id and 42 other fieldsHigh correlation
_embedded.show.image.original is highly correlated with id and 42 other fieldsHigh correlation
_embedded.show.summary is highly correlated with id and 37 other fieldsHigh correlation
_embedded.show.updated is highly correlated with id and 37 other fieldsHigh correlation
_embedded.show._links.self.href is highly correlated with id and 42 other fieldsHigh correlation
_embedded.show._links.previousepisode.href is highly correlated with id and 42 other fieldsHigh correlation
_embedded.show.webChannel.country.name is highly correlated with id and 35 other fieldsHigh correlation
_embedded.show.webChannel.country.code is highly correlated with id and 35 other fieldsHigh correlation
_embedded.show.webChannel.country.timezone is highly correlated with id and 35 other fieldsHigh correlation
image.medium is highly correlated with id and 36 other fieldsHigh correlation
image.original is highly correlated with id and 36 other fieldsHigh correlation
_embedded.show.network.id is highly correlated with id and 27 other fieldsHigh correlation
_embedded.show.network.name is highly correlated with id and 27 other fieldsHigh correlation
_embedded.show.network.country.name is highly correlated with id and 27 other fieldsHigh correlation
_embedded.show.network.country.code is highly correlated with id and 27 other fieldsHigh correlation
_embedded.show.network.country.timezone is highly correlated with id and 27 other fieldsHigh correlation
_embedded.show._links.nextepisode.href is highly correlated with id and 30 other fieldsHigh correlation
runtime has 2 (2.7%) missing values Missing
image has 74 (100.0%) missing values Missing
summary has 65 (87.8%) missing values Missing
rating.average has 72 (97.3%) missing values Missing
_embedded.show.runtime has 21 (28.4%) missing values Missing
_embedded.show.averageRuntime has 2 (2.7%) missing values Missing
_embedded.show.ended has 40 (54.1%) missing values Missing
_embedded.show.officialSite has 12 (16.2%) missing values Missing
_embedded.show.rating.average has 72 (97.3%) missing values Missing
_embedded.show.network has 74 (100.0%) missing values Missing
_embedded.show.webChannel.id has 1 (1.4%) missing values Missing
_embedded.show.webChannel.name has 1 (1.4%) missing values Missing
_embedded.show.webChannel.country has 74 (100.0%) missing values Missing
_embedded.show.webChannel.officialSite has 24 (32.4%) missing values Missing
_embedded.show.dvdCountry has 74 (100.0%) missing values Missing
_embedded.show.externals.tvrage has 73 (98.6%) missing values Missing
_embedded.show.externals.thetvdb has 30 (40.5%) missing values Missing
_embedded.show.externals.imdb has 45 (60.8%) missing values Missing
_embedded.show.image.medium has 7 (9.5%) missing values Missing
_embedded.show.image.original has 7 (9.5%) missing values Missing
_embedded.show.summary has 4 (5.4%) missing values Missing
_embedded.show.webChannel.country.name has 30 (40.5%) missing values Missing
_embedded.show.webChannel.country.code has 30 (40.5%) missing values Missing
_embedded.show.webChannel.country.timezone has 30 (40.5%) missing values Missing
image.medium has 62 (83.8%) missing values Missing
image.original has 62 (83.8%) missing values Missing
_embedded.show.network.id has 71 (95.9%) missing values Missing
_embedded.show.network.name has 71 (95.9%) missing values Missing
_embedded.show.network.country.name has 71 (95.9%) missing values Missing
_embedded.show.network.country.code has 71 (95.9%) missing values Missing
_embedded.show.network.country.timezone has 71 (95.9%) missing values Missing
_embedded.show.network.officialSite has 74 (100.0%) missing values Missing
_embedded.show._links.nextepisode.href has 69 (93.2%) missing values Missing
_embedded.show.image has 74 (100.0%) missing values Missing
_embedded.show.dvdCountry.name has 73 (98.6%) missing values Missing
_embedded.show.dvdCountry.code has 73 (98.6%) missing values Missing
_embedded.show.dvdCountry.timezone has 73 (98.6%) missing values Missing
_embedded.show.webChannel has 74 (100.0%) missing values Missing
url is uniformly distributed Uniform
name is uniformly distributed Uniform
summary is uniformly distributed Uniform
rating.average is uniformly distributed Uniform
_links.self.href is uniformly distributed Uniform
_embedded.show.rating.average is uniformly distributed Uniform
image.medium is uniformly distributed Uniform
image.original is uniformly distributed Uniform
_embedded.show.network.id is uniformly distributed Uniform
_embedded.show.network.name is uniformly distributed Uniform
_embedded.show.network.country.name is uniformly distributed Uniform
_embedded.show.network.country.code is uniformly distributed Uniform
_embedded.show.network.country.timezone is uniformly distributed Uniform
_embedded.show._links.nextepisode.href is uniformly distributed Uniform
id has unique values Unique
url has unique values Unique
_links.self.href has unique values Unique
image is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.genres is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.schedule.days is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.network is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.webChannel.country is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.dvdCountry is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.network.officialSite is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.image is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.webChannel is an unsupported type, check if it needs cleaning or further analysis Unsupported

Reproduction

Analysis started2022-09-06 02:50:29.083125
Analysis finished2022-09-06 02:50:42.818858
Duration13.74 seconds
Software versionpandas-profiling v3.2.0
Download configurationconfig.json

Variables

id
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
UNIQUE

Distinct74
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2040075.243
Minimum1960500
Maximum2379933
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size720.0 B
2022-09-05T21:50:42.889437image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1960500
5-th percentile1976050.65
Q11990437.25
median1997183.5
Q32075173.25
95-th percentile2244234.7
Maximum2379933
Range419433
Interquartile range (IQR)84736

Descriptive statistics

Standard deviation91085.39093
Coefficient of variation (CV)0.04464805464
Kurtosis4.428690347
Mean2040075.243
Median Absolute Deviation (MAD)11413
Skewness2.166974227
Sum150965568
Variance8296548441
MonotonicityNot monotonic
2022-09-05T21:50:43.016488image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20077561
 
1.4%
19938291
 
1.4%
19938271
 
1.4%
19883031
 
1.4%
19880731
 
1.4%
19880721
 
1.4%
19852051
 
1.4%
19849591
 
1.4%
19849581
 
1.4%
19760511
 
1.4%
Other values (64)64
86.5%
ValueCountFrequency (%)
19605001
1.4%
19645691
1.4%
19680041
1.4%
19760501
1.4%
19760511
1.4%
19774211
1.4%
19793061
1.4%
19804061
1.4%
19804071
1.4%
19849581
1.4%
ValueCountFrequency (%)
23799331
1.4%
23244241
1.4%
23244231
1.4%
23181151
1.4%
22044531
1.4%
21926271
1.4%
21761461
1.4%
21650091
1.4%
21614181
1.4%
21264821
1.4%

url
Categorical

HIGH CARDINALITY
HIGH CORRELATION
UNIFORM
UNIQUE

Distinct74
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size720.0 B
https://www.tvmaze.com/episodes/2007756/stand-up-autsajd-1x11-pavel-dedisev-17-minut-serebra
 
1
https://www.tvmaze.com/episodes/1993829/the-case-solver-1x23-episode-23
 
1
https://www.tvmaze.com/episodes/1993827/the-case-solver-1x21-episode-21
 
1
https://www.tvmaze.com/episodes/1988303/nwa-shockwave-1x05-episode-5
 
1
https://www.tvmaze.com/episodes/1988073/forever-love-1x22-episode-22
 
1
Other values (69)
69 

Length

Max length124
Median length95.5
Mean length81.21621622
Min length59

Characters and Unicode

Total characters6010
Distinct characters40
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique74 ?
Unique (%)100.0%

Sample

1st rowhttps://www.tvmaze.com/episodes/2007756/stand-up-autsajd-1x11-pavel-dedisev-17-minut-serebra
2nd rowhttps://www.tvmaze.com/episodes/1987860/blic-krik-1x12-12-nurlan-saburov-t-fest-garik-oganisan-rustam-reptiloid-emir-kasokov
3rd rowhttps://www.tvmaze.com/episodes/2008031/lab-s-antonom-belaevym-2x10-therr-maitz
4th rowhttps://www.tvmaze.com/episodes/1964569/core-sense-1x13-episode-13
5th rowhttps://www.tvmaze.com/episodes/2052513/wu-shen-zhu-zai-1x88-episode-88

Common Values

ValueCountFrequency (%)
https://www.tvmaze.com/episodes/2007756/stand-up-autsajd-1x11-pavel-dedisev-17-minut-serebra1
 
1.4%
https://www.tvmaze.com/episodes/1993829/the-case-solver-1x23-episode-231
 
1.4%
https://www.tvmaze.com/episodes/1993827/the-case-solver-1x21-episode-211
 
1.4%
https://www.tvmaze.com/episodes/1988303/nwa-shockwave-1x05-episode-51
 
1.4%
https://www.tvmaze.com/episodes/1988073/forever-love-1x22-episode-221
 
1.4%
https://www.tvmaze.com/episodes/1988072/forever-love-1x21-episode-211
 
1.4%
https://www.tvmaze.com/episodes/1985205/handmade-love-1x06-meet-me-in-your-past1
 
1.4%
https://www.tvmaze.com/episodes/1984959/dream-detective-1x20-episode-201
 
1.4%
https://www.tvmaze.com/episodes/1984958/dream-detective-1x19-episode-191
 
1.4%
https://www.tvmaze.com/episodes/1976051/twisted-fate-of-love-1x40-episode-401
 
1.4%
Other values (64)64
86.5%

Length

2022-09-05T21:50:43.135106image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.tvmaze.com/episodes/2007756/stand-up-autsajd-1x11-pavel-dedisev-17-minut-serebra1
 
1.4%
https://www.tvmaze.com/episodes/1997183/paurashpur-1x03-kala-ranveer-not-a-love-story1
 
1.4%
https://www.tvmaze.com/episodes/1964569/core-sense-1x13-episode-131
 
1.4%
https://www.tvmaze.com/episodes/2052513/wu-shen-zhu-zai-1x88-episode-881
 
1.4%
https://www.tvmaze.com/episodes/1993658/7-days-of-romance-2x03-episode-31
 
1.4%
https://www.tvmaze.com/episodes/2096302/no-turning-back-romance-1x07-71
 
1.4%
https://www.tvmaze.com/episodes/2324423/unique-lady-2x11-episode-111
 
1.4%
https://www.tvmaze.com/episodes/2324424/unique-lady-2x12-episode-121
 
1.4%
https://www.tvmaze.com/episodes/2068352/doomsday-awakening-2x03-episode-31
 
1.4%
https://www.tvmaze.com/episodes/1998600/unique-lady-2-1x11-episode-111
 
1.4%
Other values (64)64
86.5%

Most occurring characters

ValueCountFrequency (%)
e524
 
8.7%
-470
 
7.8%
/370
 
6.2%
t365
 
6.1%
s363
 
6.0%
o301
 
5.0%
w248
 
4.1%
i242
 
4.0%
a241
 
4.0%
p221
 
3.7%
Other values (30)2665
44.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter4060
67.6%
Decimal Number888
 
14.8%
Other Punctuation592
 
9.9%
Dash Punctuation470
 
7.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e524
12.9%
t365
 
9.0%
s363
 
8.9%
o301
 
7.4%
w248
 
6.1%
i242
 
6.0%
a241
 
5.9%
p221
 
5.4%
m197
 
4.9%
d174
 
4.3%
Other values (16)1184
29.2%
Decimal Number
ValueCountFrequency (%)
1181
20.4%
2161
18.1%
0129
14.5%
9103
11.6%
761
 
6.9%
856
 
6.3%
355
 
6.2%
451
 
5.7%
648
 
5.4%
543
 
4.8%
Other Punctuation
ValueCountFrequency (%)
/370
62.5%
.148
 
25.0%
:74
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-470
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin4060
67.6%
Common1950
32.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e524
12.9%
t365
 
9.0%
s363
 
8.9%
o301
 
7.4%
w248
 
6.1%
i242
 
6.0%
a241
 
5.9%
p221
 
5.4%
m197
 
4.9%
d174
 
4.3%
Other values (16)1184
29.2%
Common
ValueCountFrequency (%)
-470
24.1%
/370
19.0%
1181
 
9.3%
2161
 
8.3%
.148
 
7.6%
0129
 
6.6%
9103
 
5.3%
:74
 
3.8%
761
 
3.1%
856
 
2.9%
Other values (4)197
10.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII6010
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e524
 
8.7%
-470
 
7.8%
/370
 
6.2%
t365
 
6.1%
s363
 
6.0%
o301
 
5.0%
w248
 
4.1%
i242
 
4.0%
a241
 
4.0%
p221
 
3.7%
Other values (30)2665
44.3%

name
Categorical

HIGH CARDINALITY
HIGH CORRELATION
UNIFORM

Distinct61
Distinct (%)82.4%
Missing0
Missing (%)0.0%
Memory size720.0 B
Episode 3
Episode 12
 
3
Episode 2
 
2
Episode 21
 
2
Episode 22
 
2
Other values (56)
59 

Length

Max length75
Median length41
Mean length18.18918919
Min length1

Characters and Unicode

Total characters1346
Distinct characters124
Distinct categories9 ?
Distinct scripts5 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique53 ?
Unique (%)71.6%

Sample

1st rowПавел Дедищев "17 минут серебра"
2nd row#12: НУРЛАН САБУРОВ, T-Fest, ГАРИК ОГАНИСЯН, РУСТАМ РЕПТИЛОИД, ЭМИР КАШОКОВ
3rd rowTherr Maitz
4th rowEpisode 13
5th rowEpisode 88

Common Values

ValueCountFrequency (%)
Episode 36
 
8.1%
Episode 123
 
4.1%
Episode 22
 
2.7%
Episode 212
 
2.7%
Episode 222
 
2.7%
Episode 112
 
2.7%
Episode 52
 
2.7%
Episode 102
 
2.7%
AEW Dark 671
 
1.4%
Primetime Live 161
 
1.4%
Other values (51)51
68.9%

Length

2022-09-05T21:50:43.247254image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
episode36
 
15.1%
the8
 
3.3%
36
 
2.5%
124
 
1.7%
24
 
1.7%
20204
 
1.7%
in3
 
1.3%
of3
 
1.3%
er2
 
0.8%
odcinek2
 
0.8%
Other values (156)167
69.9%

Most occurring characters

ValueCountFrequency (%)
165
 
12.3%
e118
 
8.8%
o79
 
5.9%
i73
 
5.4%
s64
 
4.8%
r59
 
4.4%
d58
 
4.3%
a53
 
3.9%
p43
 
3.2%
E38
 
2.8%
Other values (114)596
44.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter837
62.2%
Uppercase Letter201
 
14.9%
Space Separator165
 
12.3%
Decimal Number95
 
7.1%
Other Punctuation24
 
1.8%
Other Letter16
 
1.2%
Dash Punctuation4
 
0.3%
Close Punctuation2
 
0.1%
Open Punctuation2
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e118
14.1%
o79
 
9.4%
i73
 
8.7%
s64
 
7.6%
r59
 
7.0%
d58
 
6.9%
a53
 
6.3%
p43
 
5.1%
n38
 
4.5%
t37
 
4.4%
Other values (38)215
25.7%
Uppercase Letter
ValueCountFrequency (%)
E38
18.9%
T15
 
7.5%
P9
 
4.5%
А8
 
4.0%
O7
 
3.5%
M7
 
3.5%
H6
 
3.0%
Р6
 
3.0%
L6
 
3.0%
C5
 
2.5%
Other values (33)94
46.8%
Other Letter
ValueCountFrequency (%)
و3
18.8%
ا2
12.5%
م1
 
6.2%
س1
 
6.2%
1
 
6.2%
1
 
6.2%
ب1
 
6.2%
ز1
 
6.2%
ی1
 
6.2%
ل1
 
6.2%
Other values (3)3
18.8%
Decimal Number
ValueCountFrequency (%)
228
29.5%
120
21.1%
012
12.6%
312
12.6%
55
 
5.3%
95
 
5.3%
65
 
5.3%
73
 
3.2%
43
 
3.2%
82
 
2.1%
Other Punctuation
ValueCountFrequency (%)
,9
37.5%
:9
37.5%
#2
 
8.3%
"2
 
8.3%
.1
 
4.2%
!1
 
4.2%
Space Separator
ValueCountFrequency (%)
165
100.0%
Dash Punctuation
ValueCountFrequency (%)
-4
100.0%
Close Punctuation
ValueCountFrequency (%)
)2
100.0%
Open Punctuation
ValueCountFrequency (%)
(2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin918
68.2%
Common292
 
21.7%
Cyrillic120
 
8.9%
Arabic14
 
1.0%
Han2
 
0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e118
 
12.9%
o79
 
8.6%
i73
 
8.0%
s64
 
7.0%
r59
 
6.4%
d58
 
6.3%
a53
 
5.8%
p43
 
4.7%
E38
 
4.1%
n38
 
4.1%
Other values (38)295
32.1%
Cyrillic
ValueCountFrequency (%)
е9
 
7.5%
А8
 
6.7%
Р6
 
5.0%
а6
 
5.0%
И5
 
4.2%
р5
 
4.2%
и5
 
4.2%
О5
 
4.2%
с4
 
3.3%
Н4
 
3.3%
Other values (33)63
52.5%
Common
ValueCountFrequency (%)
165
56.5%
228
 
9.6%
120
 
6.8%
012
 
4.1%
312
 
4.1%
,9
 
3.1%
:9
 
3.1%
55
 
1.7%
95
 
1.7%
65
 
1.7%
Other values (10)22
 
7.5%
Arabic
ValueCountFrequency (%)
و3
21.4%
ا2
14.3%
م1
 
7.1%
س1
 
7.1%
ب1
 
7.1%
ز1
 
7.1%
ی1
 
7.1%
ل1
 
7.1%
گ1
 
7.1%
ر1
 
7.1%
Han
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII1208
89.7%
Cyrillic120
 
8.9%
Arabic14
 
1.0%
None2
 
0.1%
CJK2
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
165
 
13.7%
e118
 
9.8%
o79
 
6.5%
i73
 
6.0%
s64
 
5.3%
r59
 
4.9%
d58
 
4.8%
a53
 
4.4%
p43
 
3.6%
E38
 
3.1%
Other values (57)458
37.9%
Cyrillic
ValueCountFrequency (%)
е9
 
7.5%
А8
 
6.7%
Р6
 
5.0%
а6
 
5.0%
И5
 
4.2%
р5
 
4.2%
и5
 
4.2%
О5
 
4.2%
с4
 
3.3%
Н4
 
3.3%
Other values (33)63
52.5%
Arabic
ValueCountFrequency (%)
و3
21.4%
ا2
14.3%
م1
 
7.1%
س1
 
7.1%
ب1
 
7.1%
ز1
 
7.1%
ی1
 
7.1%
ل1
 
7.1%
گ1
 
7.1%
ر1
 
7.1%
None
ValueCountFrequency (%)
å2
100.0%
CJK
ValueCountFrequency (%)
1
50.0%
1
50.0%

season
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct7
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean220.0945946
Minimum1
Maximum2020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size720.0 B
2022-09-05T21:50:43.331350image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q32
95-th percentile2020
Maximum2020
Range2019
Interquartile range (IQR)1

Descriptive statistics

Standard deviation630.9339928
Coefficient of variation (CV)2.866649197
Kurtosis4.766818701
Mean220.0945946
Median Absolute Deviation (MAD)0
Skewness2.576499543
Sum16287
Variance398077.7033
MonotonicityNot monotonic
2022-09-05T21:50:43.413233image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
145
60.8%
214
 
18.9%
20208
 
10.8%
43
 
4.1%
32
 
2.7%
51
 
1.4%
311
 
1.4%
ValueCountFrequency (%)
145
60.8%
214
 
18.9%
32
 
2.7%
43
 
4.1%
51
 
1.4%
311
 
1.4%
20208
 
10.8%
ValueCountFrequency (%)
20208
 
10.8%
311
 
1.4%
51
 
1.4%
43
 
4.1%
32
 
2.7%
214
 
18.9%
145
60.8%

number
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct33
Distinct (%)44.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean30.28378378
Minimum1
Maximum356
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size720.0 B
2022-09-05T21:50:43.503244image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median10
Q322
95-th percentile107.6
Maximum356
Range355
Interquartile range (IQR)19

Descriptive statistics

Standard deviation66.80507738
Coefficient of variation (CV)2.205968642
Kurtosis15.87764976
Mean30.28378378
Median Absolute Deviation (MAD)7.5
Skewness3.965139523
Sum2241
Variance4462.918364
MonotonicityNot monotonic
2022-09-05T21:50:43.606551image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
39
 
12.2%
16
 
8.1%
26
 
8.1%
54
 
5.4%
124
 
5.4%
64
 
5.4%
44
 
5.4%
113
 
4.1%
103
 
4.1%
72
 
2.7%
Other values (23)29
39.2%
ValueCountFrequency (%)
16
8.1%
26
8.1%
39
12.2%
44
5.4%
54
5.4%
64
5.4%
72
 
2.7%
103
 
4.1%
113
 
4.1%
124
5.4%
ValueCountFrequency (%)
3561
1.4%
3201
1.4%
3191
1.4%
1441
1.4%
881
1.4%
701
1.4%
591
1.4%
561
1.4%
532
2.7%
522
2.7%

type
Categorical

CONSTANT
REJECTED

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size720.0 B
regular
74 

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters518
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowregular
2nd rowregular
3rd rowregular
4th rowregular
5th rowregular

Common Values

ValueCountFrequency (%)
regular74
100.0%

Length

2022-09-05T21:50:43.699761image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:50:43.780684image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
regular74
100.0%

Most occurring characters

ValueCountFrequency (%)
r148
28.6%
e74
14.3%
g74
14.3%
u74
14.3%
l74
14.3%
a74
14.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter518
100.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r148
28.6%
e74
14.3%
g74
14.3%
u74
14.3%
l74
14.3%
a74
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin518
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
r148
28.6%
e74
14.3%
g74
14.3%
u74
14.3%
l74
14.3%
a74
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII518
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
r148
28.6%
e74
14.3%
g74
14.3%
u74
14.3%
l74
14.3%
a74
14.3%

airdate
Categorical

CONSTANT
REJECTED

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size720.0 B
2020-12-29
74 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters740
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-12-29
2nd row2020-12-29
3rd row2020-12-29
4th row2020-12-29
5th row2020-12-29

Common Values

ValueCountFrequency (%)
2020-12-2974
100.0%

Length

2022-09-05T21:50:43.852031image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:50:43.933630image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
2020-12-2974
100.0%

Most occurring characters

ValueCountFrequency (%)
2296
40.0%
0148
20.0%
-148
20.0%
174
 
10.0%
974
 
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number592
80.0%
Dash Punctuation148
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2296
50.0%
0148
25.0%
174
 
12.5%
974
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-148
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common740
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2296
40.0%
0148
20.0%
-148
20.0%
174
 
10.0%
974
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII740
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2296
40.0%
0148
20.0%
-148
20.0%
174
 
10.0%
974
 
10.0%

airtime
Categorical

HIGH CORRELATION

Distinct10
Distinct (%)13.5%
Missing0
Missing (%)0.0%
Memory size720.0 B
52 
20:00
12:00
 
4
21:00
 
4
10:00
 
2
Other values (5)
 
5

Length

Max length5
Median length0
Mean length1.486486486
Min length0

Characters and Unicode

Total characters110
Distinct characters7
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)6.8%

Sample

1st row12:00
2nd row12:00
3rd row
4th row10:00
5th row10:00

Common Values

ValueCountFrequency (%)
52
70.3%
20:007
 
9.5%
12:004
 
5.4%
21:004
 
5.4%
10:002
 
2.7%
08:001
 
1.4%
17:001
 
1.4%
22:001
 
1.4%
19:001
 
1.4%
18:001
 
1.4%

Length

2022-09-05T21:50:44.007976image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:50:44.115790image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
20:007
31.8%
12:004
18.2%
21:004
18.2%
10:002
 
9.1%
08:001
 
4.5%
17:001
 
4.5%
22:001
 
4.5%
19:001
 
4.5%
18:001
 
4.5%

Most occurring characters

ValueCountFrequency (%)
054
49.1%
:22
20.0%
217
 
15.5%
113
 
11.8%
82
 
1.8%
71
 
0.9%
91
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number88
80.0%
Other Punctuation22
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
054
61.4%
217
 
19.3%
113
 
14.8%
82
 
2.3%
71
 
1.1%
91
 
1.1%
Other Punctuation
ValueCountFrequency (%)
:22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common110
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
054
49.1%
:22
20.0%
217
 
15.5%
113
 
11.8%
82
 
1.8%
71
 
0.9%
91
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII110
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
054
49.1%
:22
20.0%
217
 
15.5%
113
 
11.8%
82
 
1.8%
71
 
0.9%
91
 
0.9%

airstamp
Categorical

HIGH CORRELATION

Distinct13
Distinct (%)17.6%
Missing0
Missing (%)0.0%
Memory size720.0 B
2020-12-29T12:00:00+00:00
31 
2020-12-29T11:00:00+00:00
10 
2020-12-29T04:00:00+00:00
2020-12-29T06:30:00+00:00
2020-12-29T17:00:00+00:00
Other values (8)
15 

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters1850
Distinct characters14
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)5.4%

Sample

1st row2020-12-29T00:00:00+00:00
2nd row2020-12-29T00:00:00+00:00
3rd row2020-12-29T00:00:00+00:00
4th row2020-12-29T02:00:00+00:00
5th row2020-12-29T02:00:00+00:00

Common Values

ValueCountFrequency (%)
2020-12-29T12:00:00+00:0031
41.9%
2020-12-29T11:00:00+00:0010
 
13.5%
2020-12-29T04:00:00+00:007
 
9.5%
2020-12-29T06:30:00+00:007
 
9.5%
2020-12-29T17:00:00+00:004
 
5.4%
2020-12-29T21:00:00+00:004
 
5.4%
2020-12-29T00:00:00+00:003
 
4.1%
2020-12-29T02:00:00+00:002
 
2.7%
2020-12-29T03:00:00+00:002
 
2.7%
2020-12-29T04:30:00+00:001
 
1.4%
Other values (3)3
 
4.1%

Length

2022-09-05T21:50:44.210879image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-12-29t12:00:00+00:0031
41.9%
2020-12-29t11:00:00+00:0010
 
13.5%
2020-12-29t04:00:00+00:007
 
9.5%
2020-12-29t06:30:00+00:007
 
9.5%
2020-12-29t17:00:00+00:004
 
5.4%
2020-12-29t21:00:00+00:004
 
5.4%
2020-12-29t00:00:00+00:003
 
4.1%
2020-12-29t02:00:00+00:002
 
2.7%
2020-12-29t03:00:00+00:002
 
2.7%
2020-12-29t04:30:00+00:001
 
1.4%
Other values (3)3
 
4.1%

Most occurring characters

ValueCountFrequency (%)
0758
41.0%
2333
18.0%
:222
 
12.0%
-148
 
8.0%
1135
 
7.3%
975
 
4.1%
T74
 
4.0%
+74
 
4.0%
310
 
0.5%
48
 
0.4%
Other values (4)13
 
0.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number1332
72.0%
Other Punctuation222
 
12.0%
Dash Punctuation148
 
8.0%
Uppercase Letter74
 
4.0%
Math Symbol74
 
4.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0758
56.9%
2333
25.0%
1135
 
10.1%
975
 
5.6%
310
 
0.8%
48
 
0.6%
67
 
0.5%
74
 
0.3%
81
 
0.1%
51
 
0.1%
Other Punctuation
ValueCountFrequency (%)
:222
100.0%
Dash Punctuation
ValueCountFrequency (%)
-148
100.0%
Uppercase Letter
ValueCountFrequency (%)
T74
100.0%
Math Symbol
ValueCountFrequency (%)
+74
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common1776
96.0%
Latin74
 
4.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0758
42.7%
2333
18.8%
:222
 
12.5%
-148
 
8.3%
1135
 
7.6%
975
 
4.2%
+74
 
4.2%
310
 
0.6%
48
 
0.5%
67
 
0.4%
Other values (3)6
 
0.3%
Latin
ValueCountFrequency (%)
T74
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII1850
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0758
41.0%
2333
18.0%
:222
 
12.0%
-148
 
8.0%
1135
 
7.3%
975
 
4.1%
T74
 
4.0%
+74
 
4.0%
310
 
0.5%
48
 
0.4%
Other values (4)13
 
0.7%

runtime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct28
Distinct (%)38.9%
Missing2
Missing (%)2.7%
Infinite0
Infinite (%)0.0%
Mean38.16666667
Minimum4
Maximum120
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size720.0 B
2022-09-05T21:50:44.302790image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile9.1
Q119.75
median30
Q345
95-th percentile90
Maximum120
Range116
Interquartile range (IQR)25.25

Descriptive statistics

Standard deviation26.02598918
Coefficient of variation (CV)0.6819036466
Kurtosis2.674876873
Mean38.16666667
Median Absolute Deviation (MAD)15
Skewness1.572302145
Sum2748
Variance677.3521127
MonotonicityNot monotonic
2022-09-05T21:50:44.418767image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
4513
17.6%
3010
13.5%
605
 
6.8%
904
 
5.4%
274
 
5.4%
124
 
5.4%
1203
 
4.1%
193
 
4.1%
183
 
4.1%
252
 
2.7%
Other values (18)21
28.4%
ValueCountFrequency (%)
41
 
1.4%
52
2.7%
81
 
1.4%
101
 
1.4%
124
5.4%
152
2.7%
161
 
1.4%
183
4.1%
193
4.1%
201
 
1.4%
ValueCountFrequency (%)
1203
 
4.1%
904
 
5.4%
605
 
6.8%
481
 
1.4%
4513
17.6%
431
 
1.4%
411
 
1.4%
402
 
2.7%
381
 
1.4%
371
 
1.4%

image
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing74
Missing (%)100.0%
Memory size720.0 B

summary
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct9
Distinct (%)100.0%
Missing65
Missing (%)87.8%
Memory size720.0 B
<p>Mike and the @Returning the Favor crew surprise Shelina Moreda, a motorcycle racing/model/dairy farmer's daughter who is saving animals from the wildfires and other situations in Northern California.</p>
<p>Clancy Brown (Shawshank, SpongeBob) joins me this week to share his personal experience with impostor syndrome throughout his career from its inception to highlights like The Shawshank Redemption. </p><p>Clancy talks about how the industry had changed over the decades and how he feels blessed to have found voice acting for the presence it allows him to keep. </p><p>We also get into some good ole Lex talk, how fame can drastically change a set, and even his personal experience working with the late great Sean Connery.</p>
<p>James comes out to his mother about his relationship with Sky.  The two spend quality time together at the night market and around the city.  </p>
<p>Observed at a psychiatric hospital and composed in court, the accused remains a locked box and offers few clues. Now the therapist revisits his case.</p>
<p>Claire and Eric have seemingly moved on with their lives, but a chance encounter brings new truths to light.<br /> </p>
Other values (4)

Length

Max length529
Median length172
Mean length219.5555556
Min length122

Characters and Unicode

Total characters1976
Distinct characters52
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)100.0%

Sample

1st row<p>Mike and the @Returning the Favor crew surprise Shelina Moreda, a motorcycle racing/model/dairy farmer's daughter who is saving animals from the wildfires and other situations in Northern California.</p>
2nd row<p>Clancy Brown (Shawshank, SpongeBob) joins me this week to share his personal experience with impostor syndrome throughout his career from its inception to highlights like The Shawshank Redemption. </p><p>Clancy talks about how the industry had changed over the decades and how he feels blessed to have found voice acting for the presence it allows him to keep. </p><p>We also get into some good ole Lex talk, how fame can drastically change a set, and even his personal experience working with the late great Sean Connery.</p>
3rd row<p>James comes out to his mother about his relationship with Sky.  The two spend quality time together at the night market and around the city.  </p>
4th row<p>Observed at a psychiatric hospital and composed in court, the accused remains a locked box and offers few clues. Now the therapist revisits his case.</p>
5th row<p>Claire and Eric have seemingly moved on with their lives, but a chance encounter brings new truths to light.<br /> </p>

Common Values

ValueCountFrequency (%)
<p>Mike and the @Returning the Favor crew surprise Shelina Moreda, a motorcycle racing/model/dairy farmer's daughter who is saving animals from the wildfires and other situations in Northern California.</p>1
 
1.4%
<p>Clancy Brown (Shawshank, SpongeBob) joins me this week to share his personal experience with impostor syndrome throughout his career from its inception to highlights like The Shawshank Redemption. </p><p>Clancy talks about how the industry had changed over the decades and how he feels blessed to have found voice acting for the presence it allows him to keep. </p><p>We also get into some good ole Lex talk, how fame can drastically change a set, and even his personal experience working with the late great Sean Connery.</p>1
 
1.4%
<p>James comes out to his mother about his relationship with Sky.  The two spend quality time together at the night market and around the city.  </p>1
 
1.4%
<p>Observed at a psychiatric hospital and composed in court, the accused remains a locked box and offers few clues. Now the therapist revisits his case.</p>1
 
1.4%
<p>Claire and Eric have seemingly moved on with their lives, but a chance encounter brings new truths to light.<br /> </p>1
 
1.4%
<p>The first episode examines how the Beckhams changed the model of the celebrity power couple, while the rise of reality TV led to a gigantic influx of people gaining overnight fame, fed by a press that saw an easy source of material. The programme also examines how leaked sex tapes changed the nature of celebrity scandal.</p>1
 
1.4%
<p>Charting the story of celebrity in the late noughties, this film looks at how different groups cashed in on the public's insatiable appetite for access to the famous.</p>1
 
1.4%
<p>This film tells the story of how celebrities capitalised on a digital revolution in order to sidestep the traditional routes to fame.</p>1
 
1.4%
<p>Charting the last five tumultuous years, this final episode takes us to the end of 2020 and interrogates the methods used by celebrities to get everything they want.</p>1
 
1.4%
(Missing)65
87.8%

Length

2022-09-05T21:50:44.535526image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:50:44.680012image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
the28
 
8.8%
to12
 
3.8%
and9
 
2.8%
a8
 
2.5%
of8
 
2.5%
how7
 
2.2%
his6
 
1.9%
in5
 
1.6%
with4
 
1.3%
this3
 
0.9%
Other values (202)229
71.8%

Most occurring characters

ValueCountFrequency (%)
307
15.5%
e200
 
10.1%
t140
 
7.1%
a119
 
6.0%
i117
 
5.9%
o113
 
5.7%
s103
 
5.2%
h96
 
4.9%
r89
 
4.5%
n89
 
4.5%
Other values (42)603
30.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1536
77.7%
Space Separator312
 
15.8%
Math Symbol46
 
2.3%
Other Punctuation41
 
2.1%
Uppercase Letter35
 
1.8%
Decimal Number4
 
0.2%
Close Punctuation1
 
0.1%
Open Punctuation1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e200
13.0%
t140
 
9.1%
a119
 
7.7%
i117
 
7.6%
o113
 
7.4%
s103
 
6.7%
h96
 
6.2%
r89
 
5.8%
n89
 
5.8%
l63
 
4.1%
Other values (15)407
26.5%
Uppercase Letter
ValueCountFrequency (%)
C7
20.0%
T6
17.1%
S6
17.1%
B3
8.6%
R2
 
5.7%
N2
 
5.7%
M2
 
5.7%
F1
 
2.9%
W1
 
2.9%
L1
 
2.9%
Other values (4)4
11.4%
Other Punctuation
ValueCountFrequency (%)
/14
34.1%
.14
34.1%
,10
24.4%
'2
 
4.9%
@1
 
2.4%
Space Separator
ValueCountFrequency (%)
307
98.4%
 5
 
1.6%
Math Symbol
ValueCountFrequency (%)
<23
50.0%
>23
50.0%
Decimal Number
ValueCountFrequency (%)
22
50.0%
02
50.0%
Close Punctuation
ValueCountFrequency (%)
)1
100.0%
Open Punctuation
ValueCountFrequency (%)
(1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1571
79.5%
Common405
 
20.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e200
12.7%
t140
 
8.9%
a119
 
7.6%
i117
 
7.4%
o113
 
7.2%
s103
 
6.6%
h96
 
6.1%
r89
 
5.7%
n89
 
5.7%
l63
 
4.0%
Other values (29)442
28.1%
Common
ValueCountFrequency (%)
307
75.8%
<23
 
5.7%
>23
 
5.7%
/14
 
3.5%
.14
 
3.5%
,10
 
2.5%
 5
 
1.2%
22
 
0.5%
'2
 
0.5%
02
 
0.5%
Other values (3)3
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII1971
99.7%
None5
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
307
15.6%
e200
 
10.1%
t140
 
7.1%
a119
 
6.0%
i117
 
5.9%
o113
 
5.7%
s103
 
5.2%
h96
 
4.9%
r89
 
4.5%
n89
 
4.5%
Other values (41)598
30.3%
None
ValueCountFrequency (%)
 5
100.0%

rating.average
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct2
Distinct (%)100.0%
Missing72
Missing (%)97.3%
Memory size720.0 B
8.5
7.3

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters6
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row8.5
2nd row7.3

Common Values

ValueCountFrequency (%)
8.51
 
1.4%
7.31
 
1.4%
(Missing)72
97.3%

Length

2022-09-05T21:50:44.820770image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:50:44.908766image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
8.51
50.0%
7.31
50.0%

Most occurring characters

ValueCountFrequency (%)
.2
33.3%
81
16.7%
51
16.7%
71
16.7%
31
16.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number4
66.7%
Other Punctuation2
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
81
25.0%
51
25.0%
71
25.0%
31
25.0%
Other Punctuation
ValueCountFrequency (%)
.2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common6
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
.2
33.3%
81
16.7%
51
16.7%
71
16.7%
31
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII6
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
.2
33.3%
81
16.7%
51
16.7%
71
16.7%
31
16.7%

_links.self.href
Categorical

HIGH CARDINALITY
HIGH CORRELATION
UNIFORM
UNIQUE

Distinct74
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size720.0 B
https://api.tvmaze.com/episodes/2007756
 
1
https://api.tvmaze.com/episodes/1993829
 
1
https://api.tvmaze.com/episodes/1993827
 
1
https://api.tvmaze.com/episodes/1988303
 
1
https://api.tvmaze.com/episodes/1988073
 
1
Other values (69)
69 

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters2886
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique74 ?
Unique (%)100.0%

Sample

1st rowhttps://api.tvmaze.com/episodes/2007756
2nd rowhttps://api.tvmaze.com/episodes/1987860
3rd rowhttps://api.tvmaze.com/episodes/2008031
4th rowhttps://api.tvmaze.com/episodes/1964569
5th rowhttps://api.tvmaze.com/episodes/2052513

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/episodes/20077561
 
1.4%
https://api.tvmaze.com/episodes/19938291
 
1.4%
https://api.tvmaze.com/episodes/19938271
 
1.4%
https://api.tvmaze.com/episodes/19883031
 
1.4%
https://api.tvmaze.com/episodes/19880731
 
1.4%
https://api.tvmaze.com/episodes/19880721
 
1.4%
https://api.tvmaze.com/episodes/19852051
 
1.4%
https://api.tvmaze.com/episodes/19849591
 
1.4%
https://api.tvmaze.com/episodes/19849581
 
1.4%
https://api.tvmaze.com/episodes/19760511
 
1.4%
Other values (64)64
86.5%

Length

2022-09-05T21:50:44.982732image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/20077561
 
1.4%
https://api.tvmaze.com/episodes/19971831
 
1.4%
https://api.tvmaze.com/episodes/19645691
 
1.4%
https://api.tvmaze.com/episodes/20525131
 
1.4%
https://api.tvmaze.com/episodes/19936581
 
1.4%
https://api.tvmaze.com/episodes/20963021
 
1.4%
https://api.tvmaze.com/episodes/23244231
 
1.4%
https://api.tvmaze.com/episodes/23244241
 
1.4%
https://api.tvmaze.com/episodes/20683521
 
1.4%
https://api.tvmaze.com/episodes/19986001
 
1.4%
Other values (64)64
86.5%

Most occurring characters

ValueCountFrequency (%)
/296
 
10.3%
p222
 
7.7%
s222
 
7.7%
e222
 
7.7%
t222
 
7.7%
o148
 
5.1%
a148
 
5.1%
i148
 
5.1%
.148
 
5.1%
m148
 
5.1%
Other values (16)962
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1850
64.1%
Other Punctuation518
 
17.9%
Decimal Number518
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
p222
12.0%
s222
12.0%
e222
12.0%
t222
12.0%
o148
8.0%
a148
8.0%
i148
8.0%
m148
8.0%
h74
 
4.0%
d74
 
4.0%
Other values (3)222
12.0%
Decimal Number
ValueCountFrequency (%)
987
16.8%
176
14.7%
261
11.8%
060
11.6%
754
10.4%
851
9.8%
437
7.1%
635
6.8%
531
 
6.0%
326
 
5.0%
Other Punctuation
ValueCountFrequency (%)
/296
57.1%
.148
28.6%
:74
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin1850
64.1%
Common1036
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
/296
28.6%
.148
14.3%
987
 
8.4%
176
 
7.3%
:74
 
7.1%
261
 
5.9%
060
 
5.8%
754
 
5.2%
851
 
4.9%
437
 
3.6%
Other values (3)92
 
8.9%
Latin
ValueCountFrequency (%)
p222
12.0%
s222
12.0%
e222
12.0%
t222
12.0%
o148
8.0%
a148
8.0%
i148
8.0%
m148
8.0%
h74
 
4.0%
d74
 
4.0%
Other values (3)222
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII2886
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/296
 
10.3%
p222
 
7.7%
s222
 
7.7%
e222
 
7.7%
t222
 
7.7%
o148
 
5.1%
a148
 
5.1%
i148
 
5.1%
.148
 
5.1%
m148
 
5.1%
Other values (16)962
33.3%

_embedded.show.id
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct49
Distinct (%)66.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean48378.67568
Minimum2504
Maximum63719
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size720.0 B
2022-09-05T21:50:45.084053image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum2504
5-th percentile15250
Q149516
median52655
Q352935.25
95-th percentile56655.85
Maximum63719
Range61215
Interquartile range (IQR)3419.25

Descriptive statistics

Standard deviation11870.53944
Coefficient of variation (CV)0.2453671845
Kurtosis5.144843427
Mean48378.67568
Median Absolute Deviation (MAD)1484
Skewness-2.366906926
Sum3580022
Variance140909706.6
MonotonicityNot monotonic
2022-09-05T21:50:45.208806image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
527367
 
9.5%
549556
 
8.1%
526554
 
5.4%
526614
 
5.4%
529362
 
2.7%
521042
 
2.7%
414902
 
2.7%
524002
 
2.7%
527842
 
2.7%
525242
 
2.7%
Other values (39)41
55.4%
ValueCountFrequency (%)
25041
1.4%
133811
1.4%
133921
1.4%
152502
2.7%
176331
1.4%
306061
1.4%
329801
1.4%
383391
1.4%
414902
2.7%
421211
1.4%
ValueCountFrequency (%)
637191
 
1.4%
617551
 
1.4%
586451
 
1.4%
573391
 
1.4%
562882
 
2.7%
550161
 
1.4%
550021
 
1.4%
549556
8.1%
540331
 
1.4%
536691
 
1.4%

_embedded.show.url
Categorical

HIGH CORRELATION

Distinct49
Distinct (%)66.2%
Missing0
Missing (%)0.0%
Memory size720.0 B
https://www.tvmaze.com/shows/52736/paurashpur
https://www.tvmaze.com/shows/54955/tillykke-i-skal-have-trillinger
https://www.tvmaze.com/shows/52655/the-case-solver
 
4
https://www.tvmaze.com/shows/52661/celebrity-a-21st-century-story
 
4
https://www.tvmaze.com/shows/52936/my-best-friends-story
 
2
Other values (44)
51 

Length

Max length71
Median length59
Mean length51.74324324
Min length39

Characters and Unicode

Total characters3829
Distinct characters40
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique37 ?
Unique (%)50.0%

Sample

1st rowhttps://www.tvmaze.com/shows/51065/stand-up-autsajd
2nd rowhttps://www.tvmaze.com/shows/52044/blic-krik
3rd rowhttps://www.tvmaze.com/shows/52933/lab-s-antonom-belaevym
4th rowhttps://www.tvmaze.com/shows/51336/core-sense
5th rowhttps://www.tvmaze.com/shows/54033/wu-shen-zhu-zai

Common Values

ValueCountFrequency (%)
https://www.tvmaze.com/shows/52736/paurashpur7
 
9.5%
https://www.tvmaze.com/shows/54955/tillykke-i-skal-have-trillinger6
 
8.1%
https://www.tvmaze.com/shows/52655/the-case-solver4
 
5.4%
https://www.tvmaze.com/shows/52661/celebrity-a-21st-century-story4
 
5.4%
https://www.tvmaze.com/shows/52936/my-best-friends-story2
 
2.7%
https://www.tvmaze.com/shows/52104/twisted-fate-of-love2
 
2.7%
https://www.tvmaze.com/shows/41490/unique-lady2
 
2.7%
https://www.tvmaze.com/shows/52400/dream-detective2
 
2.7%
https://www.tvmaze.com/shows/52784/unique-lady-22
 
2.7%
https://www.tvmaze.com/shows/52524/forever-love2
 
2.7%
Other values (39)41
55.4%

Length

2022-09-05T21:50:45.339202image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.tvmaze.com/shows/52736/paurashpur7
 
9.5%
https://www.tvmaze.com/shows/54955/tillykke-i-skal-have-trillinger6
 
8.1%
https://www.tvmaze.com/shows/52655/the-case-solver4
 
5.4%
https://www.tvmaze.com/shows/52661/celebrity-a-21st-century-story4
 
5.4%
https://www.tvmaze.com/shows/52784/unique-lady-22
 
2.7%
https://www.tvmaze.com/shows/56288/nieobecni2
 
2.7%
https://www.tvmaze.com/shows/52524/forever-love2
 
2.7%
https://www.tvmaze.com/shows/15250/the-young-turks2
 
2.7%
https://www.tvmaze.com/shows/52400/dream-detective2
 
2.7%
https://www.tvmaze.com/shows/41490/unique-lady2
 
2.7%
Other values (39)41
55.4%

Most occurring characters

ValueCountFrequency (%)
/370
 
9.7%
t309
 
8.1%
w306
 
8.0%
s283
 
7.4%
e208
 
5.4%
o207
 
5.4%
h184
 
4.8%
m168
 
4.4%
a164
 
4.3%
.148
 
3.9%
Other values (30)1482
38.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2716
70.9%
Other Punctuation592
 
15.5%
Decimal Number380
 
9.9%
Dash Punctuation141
 
3.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t309
11.4%
w306
11.3%
s283
10.4%
e208
 
7.7%
o207
 
7.6%
h184
 
6.8%
m168
 
6.2%
a164
 
6.0%
c103
 
3.8%
v99
 
3.6%
Other values (16)685
25.2%
Decimal Number
ValueCountFrequency (%)
587
22.9%
255
14.5%
443
11.3%
639
10.3%
338
10.0%
129
 
7.6%
026
 
6.8%
924
 
6.3%
722
 
5.8%
817
 
4.5%
Other Punctuation
ValueCountFrequency (%)
/370
62.5%
.148
 
25.0%
:74
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-141
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2716
70.9%
Common1113
29.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
t309
11.4%
w306
11.3%
s283
10.4%
e208
 
7.7%
o207
 
7.6%
h184
 
6.8%
m168
 
6.2%
a164
 
6.0%
c103
 
3.8%
v99
 
3.6%
Other values (16)685
25.2%
Common
ValueCountFrequency (%)
/370
33.2%
.148
 
13.3%
-141
 
12.7%
587
 
7.8%
:74
 
6.6%
255
 
4.9%
443
 
3.9%
639
 
3.5%
338
 
3.4%
129
 
2.6%
Other values (4)89
 
8.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII3829
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/370
 
9.7%
t309
 
8.1%
w306
 
8.0%
s283
 
7.4%
e208
 
5.4%
o207
 
5.4%
h184
 
4.8%
m168
 
4.4%
a164
 
4.3%
.148
 
3.9%
Other values (30)1482
38.7%

_embedded.show.name
Categorical

HIGH CORRELATION

Distinct49
Distinct (%)66.2%
Missing0
Missing (%)0.0%
Memory size720.0 B
Paurashpur
Tillykke, I skal have trillinger!
The Case Solver
 
4
Celebrity: A 21st-Century Story
 
4
My Best Friend's Story
 
2
Other values (44)
51 

Length

Max length36
Median length24
Mean length17.06756757
Min length6

Characters and Unicode

Total characters1263
Distinct characters80
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique37 ?
Unique (%)50.0%

Sample

1st rowStand Up Аутсайд
2nd rowБлиц-крик
3rd rowLAB с Антоном Беляевым
4th rowCore Sense
5th rowWu Shen Zhu Zai

Common Values

ValueCountFrequency (%)
Paurashpur7
 
9.5%
Tillykke, I skal have trillinger!6
 
8.1%
The Case Solver4
 
5.4%
Celebrity: A 21st-Century Story4
 
5.4%
My Best Friend's Story2
 
2.7%
Twisted Fate of Love2
 
2.7%
Unique Lady2
 
2.7%
Dream Detective2
 
2.7%
Unique Lady 22
 
2.7%
Forever Love2
 
2.7%
Other values (39)41
55.4%

Length

2022-09-05T21:50:45.468380image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the10
 
4.8%
paurashpur7
 
3.3%
trillinger6
 
2.9%
of6
 
2.9%
tillykke6
 
2.9%
story6
 
2.9%
have6
 
2.9%
skal6
 
2.9%
i6
 
2.9%
love5
 
2.4%
Other values (105)146
69.5%

Most occurring characters

ValueCountFrequency (%)
136
 
10.8%
e129
 
10.2%
r74
 
5.9%
a71
 
5.6%
i69
 
5.5%
t58
 
4.6%
o55
 
4.4%
l54
 
4.3%
n53
 
4.2%
u43
 
3.4%
Other values (70)521
41.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter911
72.1%
Uppercase Letter177
 
14.0%
Space Separator136
 
10.8%
Other Punctuation23
 
1.8%
Decimal Number11
 
0.9%
Dash Punctuation5
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e129
14.2%
r74
 
8.1%
a71
 
7.8%
i69
 
7.6%
t58
 
6.4%
o55
 
6.0%
l54
 
5.9%
n53
 
5.8%
u43
 
4.7%
s42
 
4.6%
Other values (36)263
28.9%
Uppercase Letter
ValueCountFrequency (%)
T25
14.1%
S17
 
9.6%
C15
 
8.5%
L15
 
8.5%
A15
 
8.5%
F8
 
4.5%
N8
 
4.5%
P8
 
4.5%
D8
 
4.5%
I7
 
4.0%
Other values (15)51
28.8%
Other Punctuation
ValueCountFrequency (%)
,7
30.4%
!6
26.1%
:5
21.7%
'5
21.7%
Decimal Number
ValueCountFrequency (%)
26
54.5%
14
36.4%
71
 
9.1%
Space Separator
ValueCountFrequency (%)
136
100.0%
Dash Punctuation
ValueCountFrequency (%)
-5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1043
82.6%
Common175
 
13.9%
Cyrillic45
 
3.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e129
 
12.4%
r74
 
7.1%
a71
 
6.8%
i69
 
6.6%
t58
 
5.6%
o55
 
5.3%
l54
 
5.2%
n53
 
5.1%
u43
 
4.1%
s42
 
4.0%
Other values (37)395
37.9%
Cyrillic
ValueCountFrequency (%)
т4
 
8.9%
и4
 
8.9%
о4
 
8.9%
к3
 
6.7%
р3
 
6.7%
н2
 
4.4%
А2
 
4.4%
е2
 
4.4%
Б2
 
4.4%
м2
 
4.4%
Other values (14)17
37.8%
Common
ValueCountFrequency (%)
136
77.7%
,7
 
4.0%
26
 
3.4%
!6
 
3.4%
-5
 
2.9%
:5
 
2.9%
'5
 
2.9%
14
 
2.3%
71
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII1218
96.4%
Cyrillic45
 
3.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
136
 
11.2%
e129
 
10.6%
r74
 
6.1%
a71
 
5.8%
i69
 
5.7%
t58
 
4.8%
o55
 
4.5%
l54
 
4.4%
n53
 
4.4%
u43
 
3.5%
Other values (46)476
39.1%
Cyrillic
ValueCountFrequency (%)
т4
 
8.9%
и4
 
8.9%
о4
 
8.9%
к3
 
6.7%
р3
 
6.7%
н2
 
4.4%
А2
 
4.4%
е2
 
4.4%
Б2
 
4.4%
м2
 
4.4%
Other values (14)17
37.8%

_embedded.show.type
Categorical

HIGH CORRELATION

Distinct9
Distinct (%)12.2%
Missing0
Missing (%)0.0%
Memory size720.0 B
Scripted
39 
Documentary
14 
Animation
Reality
News
 
3
Other values (4)

Length

Max length11
Median length8
Mean length8.364864865
Min length4

Characters and Unicode

Total characters619
Distinct characters27
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowVariety
2nd rowGame Show
3rd rowDocumentary
4th rowAnimation
5th rowAnimation

Common Values

ValueCountFrequency (%)
Scripted39
52.7%
Documentary14
 
18.9%
Animation5
 
6.8%
Reality4
 
5.4%
News3
 
4.1%
Sports3
 
4.1%
Variety2
 
2.7%
Game Show2
 
2.7%
Talk Show2
 
2.7%

Length

2022-09-05T21:50:45.591461image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:50:45.718014image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
scripted39
50.0%
documentary14
 
17.9%
animation5
 
6.4%
reality4
 
5.1%
show4
 
5.1%
news3
 
3.8%
sports3
 
3.8%
variety2
 
2.6%
game2
 
2.6%
talk2
 
2.6%

Most occurring characters

ValueCountFrequency (%)
t67
10.8%
e64
10.3%
r58
9.4%
i55
 
8.9%
c53
 
8.6%
S46
 
7.4%
p42
 
6.8%
d39
 
6.3%
a29
 
4.7%
o26
 
4.2%
Other values (17)140
22.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter537
86.8%
Uppercase Letter78
 
12.6%
Space Separator4
 
0.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t67
12.5%
e64
11.9%
r58
10.8%
i55
10.2%
c53
9.9%
p42
7.8%
d39
7.3%
a29
 
5.4%
o26
 
4.8%
n24
 
4.5%
Other values (8)80
14.9%
Uppercase Letter
ValueCountFrequency (%)
S46
59.0%
D14
 
17.9%
A5
 
6.4%
R4
 
5.1%
N3
 
3.8%
G2
 
2.6%
V2
 
2.6%
T2
 
2.6%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin615
99.4%
Common4
 
0.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
t67
10.9%
e64
10.4%
r58
9.4%
i55
8.9%
c53
 
8.6%
S46
 
7.5%
p42
 
6.8%
d39
 
6.3%
a29
 
4.7%
o26
 
4.2%
Other values (16)136
22.1%
Common
ValueCountFrequency (%)
4
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII619
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t67
10.8%
e64
10.3%
r58
9.4%
i55
 
8.9%
c53
 
8.6%
S46
 
7.4%
p42
 
6.8%
d39
 
6.3%
a29
 
4.7%
o26
 
4.2%
Other values (17)140
22.6%

_embedded.show.language
Categorical

HIGH CORRELATION

Distinct15
Distinct (%)20.3%
Missing0
Missing (%)0.0%
Memory size720.0 B
Chinese
22 
English
17 
Hindi
Danish
Korean
Other values (10)
18 

Length

Max length10
Median length7
Mean length6.675675676
Min length4

Characters and Unicode

Total characters494
Distinct characters30
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)6.8%

Sample

1st rowRussian
2nd rowRussian
3rd rowRussian
4th rowChinese
5th rowChinese

Common Values

ValueCountFrequency (%)
Chinese22
29.7%
English17
23.0%
Hindi7
 
9.5%
Danish6
 
8.1%
Korean4
 
5.4%
Norwegian4
 
5.4%
Russian3
 
4.1%
Polish2
 
2.7%
Thai2
 
2.7%
Arabic2
 
2.7%
Other values (5)5
 
6.8%

Length

2022-09-05T21:50:45.819707image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
chinese22
29.7%
english17
23.0%
hindi7
 
9.5%
danish6
 
8.1%
korean4
 
5.4%
norwegian4
 
5.4%
russian3
 
4.1%
polish2
 
2.7%
thai2
 
2.7%
arabic2
 
2.7%
Other values (5)5
 
6.8%

Most occurring characters

ValueCountFrequency (%)
i76
15.4%
n67
13.6%
e58
11.7%
s55
11.1%
h50
10.1%
a25
 
5.1%
C22
 
4.5%
g21
 
4.3%
l19
 
3.8%
E17
 
3.4%
Other values (20)84
17.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter420
85.0%
Uppercase Letter74
 
15.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i76
18.1%
n67
16.0%
e58
13.8%
s55
13.1%
h50
11.9%
a25
 
6.0%
g21
 
5.0%
l19
 
4.5%
r13
 
3.1%
o10
 
2.4%
Other values (8)26
 
6.2%
Uppercase Letter
ValueCountFrequency (%)
C22
29.7%
E17
23.0%
H8
 
10.8%
D7
 
9.5%
K4
 
5.4%
N4
 
5.4%
P3
 
4.1%
R3
 
4.1%
A2
 
2.7%
T2
 
2.7%
Other values (2)2
 
2.7%

Most occurring scripts

ValueCountFrequency (%)
Latin494
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
i76
15.4%
n67
13.6%
e58
11.7%
s55
11.1%
h50
10.1%
a25
 
5.1%
C22
 
4.5%
g21
 
4.3%
l19
 
3.8%
E17
 
3.4%
Other values (20)84
17.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII494
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i76
15.4%
n67
13.6%
e58
11.7%
s55
11.1%
h50
10.1%
a25
 
5.1%
C22
 
4.5%
g21
 
4.3%
l19
 
3.8%
E17
 
3.4%
Other values (20)84
17.0%

_embedded.show.genres
Unsupported

REJECTED
UNSUPPORTED

Missing0
Missing (%)0.0%
Memory size720.0 B

_embedded.show.status
Categorical

HIGH CORRELATION

Distinct3
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Memory size720.0 B
Ended
34 
Running
27 
To Be Determined
13 

Length

Max length16
Median length7
Mean length7.662162162
Min length5

Characters and Unicode

Total characters567
Distinct characters16
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowEnded
2nd rowRunning
3rd rowTo Be Determined
4th rowRunning
5th rowRunning

Common Values

ValueCountFrequency (%)
Ended34
45.9%
Running27
36.5%
To Be Determined13
 
17.6%

Length

2022-09-05T21:50:45.908058image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:50:46.002487image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
ended34
34.0%
running27
27.0%
to13
 
13.0%
be13
 
13.0%
determined13
 
13.0%

Most occurring characters

ValueCountFrequency (%)
n128
22.6%
e86
15.2%
d81
14.3%
i40
 
7.1%
E34
 
6.0%
R27
 
4.8%
u27
 
4.8%
g27
 
4.8%
26
 
4.6%
T13
 
2.3%
Other values (6)78
13.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter441
77.8%
Uppercase Letter100
 
17.6%
Space Separator26
 
4.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n128
29.0%
e86
19.5%
d81
18.4%
i40
 
9.1%
u27
 
6.1%
g27
 
6.1%
o13
 
2.9%
t13
 
2.9%
r13
 
2.9%
m13
 
2.9%
Uppercase Letter
ValueCountFrequency (%)
E34
34.0%
R27
27.0%
T13
 
13.0%
B13
 
13.0%
D13
 
13.0%
Space Separator
ValueCountFrequency (%)
26
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin541
95.4%
Common26
 
4.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
n128
23.7%
e86
15.9%
d81
15.0%
i40
 
7.4%
E34
 
6.3%
R27
 
5.0%
u27
 
5.0%
g27
 
5.0%
T13
 
2.4%
o13
 
2.4%
Other values (5)65
12.0%
Common
ValueCountFrequency (%)
26
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII567
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n128
22.6%
e86
15.2%
d81
14.3%
i40
 
7.1%
E34
 
6.0%
R27
 
4.8%
u27
 
4.8%
g27
 
4.8%
26
 
4.6%
T13
 
2.3%
Other values (6)78
13.8%

_embedded.show.runtime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct19
Distinct (%)35.8%
Missing21
Missing (%)28.4%
Infinite0
Infinite (%)0.0%
Mean41.58490566
Minimum4
Maximum120
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size720.0 B
2022-09-05T21:50:46.076961image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile9.2
Q130
median38
Q345
95-th percentile102
Maximum120
Range116
Interquartile range (IQR)15

Descriptive statistics

Standard deviation26.24106732
Coefficient of variation (CV)0.6310238511
Kurtosis2.925852999
Mean41.58490566
Median Absolute Deviation (MAD)8
Skewness1.554330739
Sum2204
Variance688.5936139
MonotonicityNot monotonic
2022-09-05T21:50:46.174958image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
4513
17.6%
308
 
10.8%
605
 
6.8%
344
 
5.4%
1203
 
4.1%
402
 
2.7%
122
 
2.7%
382
 
2.7%
152
 
2.7%
252
 
2.7%
Other values (9)10
13.5%
(Missing)21
28.4%
ValueCountFrequency (%)
41
1.4%
51
1.4%
81
1.4%
101
1.4%
122
2.7%
152
2.7%
231
1.4%
241
1.4%
252
2.7%
261
1.4%
ValueCountFrequency (%)
1203
 
4.1%
902
 
2.7%
605
 
6.8%
4513
17.6%
431
 
1.4%
402
 
2.7%
382
 
2.7%
344
 
5.4%
308
10.8%
261
 
1.4%

_embedded.show.averageRuntime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct26
Distinct (%)36.1%
Missing2
Missing (%)2.7%
Infinite0
Infinite (%)0.0%
Mean37.51388889
Minimum4
Maximum120
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size720.0 B
2022-09-05T21:50:46.265924image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile8.55
Q120
median30
Q345
95-th percentile90
Maximum120
Range116
Interquartile range (IQR)25

Descriptive statistics

Standard deviation26.06329947
Coefficient of variation (CV)0.6947639991
Kurtosis2.768410227
Mean37.51388889
Median Absolute Deviation (MAD)14
Skewness1.612532918
Sum2701
Variance679.295579
MonotonicityNot monotonic
2022-09-05T21:50:46.373164image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
3012
16.2%
4512
16.2%
207
9.5%
605
 
6.8%
124
 
5.4%
424
 
5.4%
903
 
4.1%
253
 
4.1%
1203
 
4.1%
282
 
2.7%
Other values (16)17
23.0%
ValueCountFrequency (%)
41
 
1.4%
51
 
1.4%
61
 
1.4%
81
 
1.4%
91
 
1.4%
101
 
1.4%
124
5.4%
152
 
2.7%
171
 
1.4%
207
9.5%
ValueCountFrequency (%)
1203
 
4.1%
903
 
4.1%
871
 
1.4%
605
6.8%
4512
16.2%
424
 
5.4%
401
 
1.4%
361
 
1.4%
331
 
1.4%
3012
16.2%

_embedded.show.premiered
Categorical

HIGH CORRELATION

Distinct40
Distinct (%)54.1%
Missing0
Missing (%)0.0%
Memory size720.0 B
2020-12-29
14 
2019-08-22
2020-12-21
2020-12-08
 
3
2020-12-22
 
2
Other values (35)
44 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters740
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)35.1%

Sample

1st row2020-10-13
2nd row2019-08-20
3rd row2019-12-17
4th row2020-10-13
5th row2020-03-08

Common Values

ValueCountFrequency (%)
2020-12-2914
18.9%
2019-08-226
 
8.1%
2020-12-215
 
6.8%
2020-12-083
 
4.1%
2020-12-222
 
2.7%
2020-11-232
 
2.7%
2020-12-142
 
2.7%
2013-12-242
 
2.7%
2020-12-282
 
2.7%
2020-12-272
 
2.7%
Other values (30)34
45.9%

Length

2022-09-05T21:50:46.473297image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-12-2914
18.9%
2019-08-226
 
8.1%
2020-12-215
 
6.8%
2020-12-083
 
4.1%
2020-12-272
 
2.7%
2019-01-172
 
2.7%
2020-12-242
 
2.7%
2020-10-132
 
2.7%
2019-10-082
 
2.7%
2020-12-282
 
2.7%
Other values (30)34
45.9%

Most occurring characters

ValueCountFrequency (%)
2216
29.2%
0165
22.3%
-148
20.0%
1113
15.3%
938
 
5.1%
823
 
3.1%
312
 
1.6%
710
 
1.4%
48
 
1.1%
56
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number592
80.0%
Dash Punctuation148
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2216
36.5%
0165
27.9%
1113
19.1%
938
 
6.4%
823
 
3.9%
312
 
2.0%
710
 
1.7%
48
 
1.4%
56
 
1.0%
61
 
0.2%
Dash Punctuation
ValueCountFrequency (%)
-148
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common740
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2216
29.2%
0165
22.3%
-148
20.0%
1113
15.3%
938
 
5.1%
823
 
3.1%
312
 
1.6%
710
 
1.4%
48
 
1.1%
56
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII740
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2216
29.2%
0165
22.3%
-148
20.0%
1113
15.3%
938
 
5.1%
823
 
3.1%
312
 
1.6%
710
 
1.4%
48
 
1.1%
56
 
0.8%

_embedded.show.ended
Categorical

HIGH CORRELATION
MISSING

Distinct12
Distinct (%)35.3%
Missing40
Missing (%)54.1%
Memory size720.0 B
2020-12-29
2021-01-05
2021-01-07
2022-05-02
2020-12-30
Other values (7)

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters340
Distinct characters9
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)14.7%

Sample

1st row2020-12-31
2nd row2021-01-20
3rd row2021-01-06
4th row2021-01-07
5th row2021-01-07

Common Values

ValueCountFrequency (%)
2020-12-299
 
12.2%
2021-01-055
 
6.8%
2021-01-074
 
5.4%
2022-05-024
 
5.4%
2020-12-303
 
4.1%
2020-12-312
 
2.7%
2021-01-152
 
2.7%
2021-01-201
 
1.4%
2021-01-061
 
1.4%
2021-02-161
 
1.4%
Other values (2)2
 
2.7%
(Missing)40
54.1%

Length

2022-09-05T21:50:46.565573image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-12-299
26.5%
2021-01-055
14.7%
2021-01-074
11.8%
2022-05-024
11.8%
2020-12-303
 
8.8%
2020-12-312
 
5.9%
2021-01-152
 
5.9%
2021-01-201
 
2.9%
2021-01-061
 
2.9%
2021-02-161
 
2.9%
Other values (2)2
 
5.9%

Most occurring characters

ValueCountFrequency (%)
2102
30.0%
087
25.6%
-68
20.0%
149
14.4%
911
 
3.2%
511
 
3.2%
36
 
1.8%
74
 
1.2%
62
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number272
80.0%
Dash Punctuation68
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2102
37.5%
087
32.0%
149
18.0%
911
 
4.0%
511
 
4.0%
36
 
2.2%
74
 
1.5%
62
 
0.7%
Dash Punctuation
ValueCountFrequency (%)
-68
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common340
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2102
30.0%
087
25.6%
-68
20.0%
149
14.4%
911
 
3.2%
511
 
3.2%
36
 
1.8%
74
 
1.2%
62
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII340
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2102
30.0%
087
25.6%
-68
20.0%
149
14.4%
911
 
3.2%
511
 
3.2%
36
 
1.8%
74
 
1.2%
62
 
0.6%

_embedded.show.officialSite
Categorical

HIGH CORRELATION
MISSING

Distinct40
Distinct (%)64.5%
Missing12
Missing (%)16.2%
Memory size720.0 B
https://www.altbalaji.com/show/paurashpur/347
https://www.dr.dk/drtv/episode/tillykke-i-skal-have-trillinger_130555
https://www.bbc.co.uk/programmes/m000qsk1
https://www.iqiyi.com/a_c4m3iuc94t.html
https://v.qq.com/x/search/?q=+%E4%BB%8A%E5%A4%95%E4%BD%95%E5%A4%95&stag=0&smartbox_ab=
 
2
Other values (35)
39 

Length

Max length86
Median length64
Mean length48.5483871
Min length18

Characters and Unicode

Total characters3010
Distinct characters74
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)50.0%

Sample

1st rowhttps://premier.one/show/13734
2nd rowhttps://the-hole.tv/shows/blitz-krik
3rd rowhttps://premier.one/show/lab-laboratoriya-muzyki-antona-belyaeva
4th rowhttps://www.bilibili.com/bangumi/media/md28223064
5th rowhttps://v.qq.com/detail/m/7q544xyrava3vxf.html

Common Values

ValueCountFrequency (%)
https://www.altbalaji.com/show/paurashpur/3477
 
9.5%
https://www.dr.dk/drtv/episode/tillykke-i-skal-have-trillinger_1305556
 
8.1%
https://www.bbc.co.uk/programmes/m000qsk14
 
5.4%
https://www.iqiyi.com/a_c4m3iuc94t.html4
 
5.4%
https://v.qq.com/x/search/?q=+%E4%BB%8A%E5%A4%95%E4%BD%95%E5%A4%95&stag=0&smartbox_ab=2
 
2.7%
https://v.qq.com/detail/m/mzc00200ur8p8zp.html2
 
2.7%
http://www.iqiyi.com/a_19rrhvpyyp.html2
 
2.7%
https://v.qq.com/detail/m/mzc00200dnvb1wh.html2
 
2.7%
https://www.tytnetwork.com2
 
2.7%
https://www.youtube.com/playlist?list=PLRXdsS5E_8i3FJ_o7VF0TFb9SUdWk54iW1
 
1.4%
Other values (30)30
40.5%
(Missing)12
 
16.2%

Length

2022-09-05T21:50:46.665948image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.altbalaji.com/show/paurashpur/3477
 
11.3%
https://www.dr.dk/drtv/episode/tillykke-i-skal-have-trillinger_1305556
 
9.7%
https://www.bbc.co.uk/programmes/m000qsk14
 
6.5%
https://www.iqiyi.com/a_c4m3iuc94t.html4
 
6.5%
https://v.qq.com/x/search/?q=+%e4%bb%8a%e5%a4%95%e4%bd%95%e5%a4%95&stag=0&smartbox_ab2
 
3.2%
https://v.qq.com/detail/m/mzc00200ur8p8zp.html2
 
3.2%
http://www.iqiyi.com/a_19rrhvpyyp.html2
 
3.2%
https://v.qq.com/detail/m/mzc00200dnvb1wh.html2
 
3.2%
https://www.tytnetwork.com2
 
3.2%
https://tv.nrk.no/serie/labyrint1
 
1.6%
Other values (30)30
48.4%

Most occurring characters

ValueCountFrequency (%)
/260
 
8.6%
t240
 
8.0%
s148
 
4.9%
.135
 
4.5%
w134
 
4.5%
a124
 
4.1%
i122
 
4.1%
h121
 
4.0%
e117
 
3.9%
o115
 
3.8%
Other values (64)1494
49.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2056
68.3%
Other Punctuation497
 
16.5%
Decimal Number266
 
8.8%
Uppercase Letter109
 
3.6%
Dash Punctuation50
 
1.7%
Connector Punctuation19
 
0.6%
Math Symbol13
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t240
 
11.7%
s148
 
7.2%
w134
 
6.5%
a124
 
6.0%
i122
 
5.9%
h121
 
5.9%
e117
 
5.7%
o115
 
5.6%
p111
 
5.4%
l109
 
5.3%
Other values (16)715
34.8%
Uppercase Letter
ValueCountFrequency (%)
E13
11.9%
A10
 
9.2%
B8
 
7.3%
L8
 
7.3%
W8
 
7.3%
P7
 
6.4%
F7
 
6.4%
C6
 
5.5%
R5
 
4.6%
D5
 
4.6%
Other values (15)32
29.4%
Decimal Number
ValueCountFrequency (%)
043
16.2%
437
13.9%
537
13.9%
330
11.3%
128
10.5%
223
8.6%
919
7.1%
718
6.8%
818
6.8%
613
 
4.9%
Other Punctuation
ValueCountFrequency (%)
/260
52.3%
.135
27.2%
:62
 
12.5%
%25
 
5.0%
?7
 
1.4%
&4
 
0.8%
'2
 
0.4%
#1
 
0.2%
!1
 
0.2%
Math Symbol
ValueCountFrequency (%)
=11
84.6%
+2
 
15.4%
Dash Punctuation
ValueCountFrequency (%)
-50
100.0%
Connector Punctuation
ValueCountFrequency (%)
_19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2165
71.9%
Common845
 
28.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
t240
 
11.1%
s148
 
6.8%
w134
 
6.2%
a124
 
5.7%
i122
 
5.6%
h121
 
5.6%
e117
 
5.4%
o115
 
5.3%
p111
 
5.1%
l109
 
5.0%
Other values (41)824
38.1%
Common
ValueCountFrequency (%)
/260
30.8%
.135
16.0%
:62
 
7.3%
-50
 
5.9%
043
 
5.1%
437
 
4.4%
537
 
4.4%
330
 
3.6%
128
 
3.3%
%25
 
3.0%
Other values (13)138
16.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII3010
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/260
 
8.6%
t240
 
8.0%
s148
 
4.9%
.135
 
4.5%
w134
 
4.5%
a124
 
4.1%
i122
 
4.1%
h121
 
4.0%
e117
 
3.9%
o115
 
3.8%
Other values (64)1494
49.6%

_embedded.show.schedule.time
Categorical

HIGH CORRELATION

Distinct10
Distinct (%)13.5%
Missing0
Missing (%)0.0%
Memory size720.0 B
54 
20:00
21:00
 
4
10:00
 
2
19:00
 
2
Other values (5)
 
5

Length

Max length5
Median length0
Mean length1.351351351
Min length0

Characters and Unicode

Total characters100
Distinct characters10
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)6.8%

Sample

1st row
2nd row
3rd row23:45
4th row10:00
5th row10:00

Common Values

ValueCountFrequency (%)
54
73.0%
20:007
 
9.5%
21:004
 
5.4%
10:002
 
2.7%
19:002
 
2.7%
23:451
 
1.4%
08:001
 
1.4%
17:001
 
1.4%
22:001
 
1.4%
18:001
 
1.4%

Length

2022-09-05T21:50:46.757862image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:50:46.861609image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
20:007
35.0%
21:004
20.0%
10:002
 
10.0%
19:002
 
10.0%
23:451
 
5.0%
08:001
 
5.0%
17:001
 
5.0%
22:001
 
5.0%
18:001
 
5.0%

Most occurring characters

ValueCountFrequency (%)
048
48.0%
:20
20.0%
214
 
14.0%
110
 
10.0%
92
 
2.0%
82
 
2.0%
31
 
1.0%
41
 
1.0%
51
 
1.0%
71
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number80
80.0%
Other Punctuation20
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
048
60.0%
214
 
17.5%
110
 
12.5%
92
 
2.5%
82
 
2.5%
31
 
1.2%
41
 
1.2%
51
 
1.2%
71
 
1.2%
Other Punctuation
ValueCountFrequency (%)
:20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common100
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
048
48.0%
:20
20.0%
214
 
14.0%
110
 
10.0%
92
 
2.0%
82
 
2.0%
31
 
1.0%
41
 
1.0%
51
 
1.0%
71
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII100
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
048
48.0%
:20
20.0%
214
 
14.0%
110
 
10.0%
92
 
2.0%
82
 
2.0%
31
 
1.0%
41
 
1.0%
51
 
1.0%
71
 
1.0%

_embedded.show.schedule.days
Unsupported

REJECTED
UNSUPPORTED

Missing0
Missing (%)0.0%
Memory size720.0 B

_embedded.show.rating.average
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct2
Distinct (%)100.0%
Missing72
Missing (%)97.3%
Memory size720.0 B
7.8
5.8

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters6
Distinct characters4
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row7.8
2nd row5.8

Common Values

ValueCountFrequency (%)
7.81
 
1.4%
5.81
 
1.4%
(Missing)72
97.3%

Length

2022-09-05T21:50:46.957280image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:50:47.055482image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
7.81
50.0%
5.81
50.0%

Most occurring characters

ValueCountFrequency (%)
.2
33.3%
82
33.3%
71
16.7%
51
16.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number4
66.7%
Other Punctuation2
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
82
50.0%
71
25.0%
51
25.0%
Other Punctuation
ValueCountFrequency (%)
.2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common6
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
.2
33.3%
82
33.3%
71
16.7%
51
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII6
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
.2
33.3%
82
33.3%
71
16.7%
51
16.7%

_embedded.show.weight
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct35
Distinct (%)47.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean30.56756757
Minimum3
Maximum94
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size720.0 B
2022-09-05T21:50:47.148853image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile4.65
Q121
median27
Q334
95-th percentile80.35
Maximum94
Range91
Interquartile range (IQR)13

Descriptive statistics

Standard deviation21.17835615
Coefficient of variation (CV)0.6928374692
Kurtosis1.343894903
Mean30.56756757
Median Absolute Deviation (MAD)7
Skewness1.311823561
Sum2262
Variance448.5227693
MonotonicityNot monotonic
2022-09-05T21:50:47.261574image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
2113
17.6%
76
 
8.1%
276
 
8.1%
345
 
6.8%
284
 
5.4%
303
 
4.1%
43
 
4.1%
352
 
2.7%
232
 
2.7%
192
 
2.7%
Other values (25)28
37.8%
ValueCountFrequency (%)
31
 
1.4%
43
 
4.1%
51
 
1.4%
76
8.1%
81
 
1.4%
131
 
1.4%
151
 
1.4%
192
 
2.7%
201
 
1.4%
2113
17.6%
ValueCountFrequency (%)
941
1.4%
831
1.4%
821
1.4%
811
1.4%
801
1.4%
761
1.4%
751
1.4%
691
1.4%
621
1.4%
601
1.4%

_embedded.show.network
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing74
Missing (%)100.0%
Memory size720.0 B

_embedded.show.webChannel.id
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct27
Distinct (%)37.0%
Missing1
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean190.1506849
Minimum1
Maximum529
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size720.0 B
2022-09-05T21:50:47.352848image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile21
Q126
median104
Q3335
95-th percentile479.8
Maximum529
Range528
Interquartile range (IQR)309

Descriptive statistics

Standard deviation171.7768798
Coefficient of variation (CV)0.9033723956
Kurtosis-1.19762579
Mean190.1506849
Median Absolute Deviation (MAD)83
Skewness0.5980890191
Sum13881
Variance29507.29642
MonotonicityNot monotonic
2022-09-05T21:50:47.457203image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
2113
17.6%
1049
12.2%
678
10.8%
3357
 
9.5%
4716
 
8.1%
264
 
5.4%
2022
 
2.7%
4932
 
2.7%
3792
 
2.7%
2382
 
2.7%
Other values (17)18
24.3%
ValueCountFrequency (%)
11
 
1.4%
21
 
1.4%
2113
17.6%
264
 
5.4%
301
 
1.4%
511
 
1.4%
678
10.8%
881
 
1.4%
1021
 
1.4%
1049
12.2%
ValueCountFrequency (%)
5291
 
1.4%
5071
 
1.4%
4932
 
2.7%
4716
8.1%
4451
 
1.4%
3811
 
1.4%
3801
 
1.4%
3792
 
2.7%
3721
 
1.4%
3357
9.5%

_embedded.show.webChannel.name
Categorical

HIGH CORRELATION
MISSING

Distinct27
Distinct (%)37.0%
Missing1
Missing (%)1.4%
Memory size720.0 B
YouTube
13 
Tencent QQ
iQIYI
ALT Balaji
DR TV
Other values (22)
30 

Length

Max length14
Median length11
Mean length7.657534247
Min length4

Characters and Unicode

Total characters559
Distinct characters52
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)21.9%

Sample

1st rowYouTube
2nd rowThe Hole
3rd rowКиноПоиск HD
4th rowBilibili
5th rowTencent QQ

Common Values

ValueCountFrequency (%)
YouTube13
17.6%
Tencent QQ9
12.2%
iQIYI8
10.8%
ALT Balaji7
 
9.5%
DR TV6
 
8.1%
BBC iPlayer4
 
5.4%
Facebook Watch2
 
2.7%
Player2
 
2.7%
Shahid2
 
2.7%
NRK TV2
 
2.7%
Other values (17)18
24.3%

Length

2022-09-05T21:50:47.564962image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
youtube13
 
11.6%
tv12
 
10.7%
qq9
 
8.0%
tencent9
 
8.0%
iqiyi8
 
7.1%
alt7
 
6.2%
balaji7
 
6.2%
dr6
 
5.4%
bbc4
 
3.6%
iplayer4
 
3.6%
Other values (26)33
29.5%

Most occurring characters

ValueCountFrequency (%)
e47
 
8.4%
T46
 
8.2%
39
 
7.0%
a32
 
5.7%
u32
 
5.7%
i31
 
5.5%
Q26
 
4.7%
o23
 
4.1%
Y23
 
4.1%
l21
 
3.8%
Other values (42)239
42.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter306
54.7%
Uppercase Letter212
37.9%
Space Separator39
 
7.0%
Math Symbol1
 
0.2%
Decimal Number1
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e47
15.4%
a32
10.5%
u32
10.5%
i31
10.1%
o23
7.5%
l21
 
6.9%
n19
 
6.2%
b16
 
5.2%
t15
 
4.9%
c14
 
4.6%
Other values (18)56
18.3%
Uppercase Letter
ValueCountFrequency (%)
T46
21.7%
Q26
12.3%
Y23
10.8%
I19
9.0%
B16
 
7.5%
V14
 
6.6%
P8
 
3.8%
R8
 
3.8%
L8
 
3.8%
A8
 
3.8%
Other values (11)36
17.0%
Space Separator
ValueCountFrequency (%)
39
100.0%
Math Symbol
ValueCountFrequency (%)
+1
100.0%
Decimal Number
ValueCountFrequency (%)
21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin509
91.1%
Common41
 
7.3%
Cyrillic9
 
1.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e47
 
9.2%
T46
 
9.0%
a32
 
6.3%
u32
 
6.3%
i31
 
6.1%
Q26
 
5.1%
o23
 
4.5%
Y23
 
4.5%
l21
 
4.1%
n19
 
3.7%
Other values (32)209
41.1%
Cyrillic
ValueCountFrequency (%)
и2
22.2%
о2
22.2%
к1
11.1%
с1
11.1%
П1
11.1%
н1
11.1%
К1
11.1%
Common
ValueCountFrequency (%)
39
95.1%
+1
 
2.4%
21
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII550
98.4%
Cyrillic9
 
1.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e47
 
8.5%
T46
 
8.4%
39
 
7.1%
a32
 
5.8%
u32
 
5.8%
i31
 
5.6%
Q26
 
4.7%
o23
 
4.2%
Y23
 
4.2%
l21
 
3.8%
Other values (35)230
41.8%
Cyrillic
ValueCountFrequency (%)
и2
22.2%
о2
22.2%
к1
11.1%
с1
11.1%
П1
11.1%
н1
11.1%
К1
11.1%

_embedded.show.webChannel.country
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing74
Missing (%)100.0%
Memory size720.0 B

_embedded.show.webChannel.officialSite
Categorical

HIGH CORRELATION
MISSING

Distinct15
Distinct (%)30.0%
Missing24
Missing (%)32.4%
Memory size720.0 B
https://www.youtube.com
13 
https://v.qq.com/
https://www.iq.com/
https://dr.dk/drtv
https://www.bbc.co.uk/iplayer
Other values (10)
10 

Length

Max length33
Median length29
Mean length21.42
Min length17

Characters and Unicode

Total characters1071
Distinct characters28
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)20.0%

Sample

1st rowhttps://www.youtube.com
2nd rowhttps://the-hole.tv/
3rd rowhttps://hd.kinopoisk.ru/
4th rowhttps://v.qq.com/
5th rowhttps://www.seezntv.com/

Common Values

ValueCountFrequency (%)
https://www.youtube.com13
17.6%
https://v.qq.com/9
 
12.2%
https://www.iq.com/8
 
10.8%
https://dr.dk/drtv6
 
8.1%
https://www.bbc.co.uk/iplayer4
 
5.4%
https://the-hole.tv/1
 
1.4%
https://hd.kinopoisk.ru/1
 
1.4%
https://www.seezntv.com/1
 
1.4%
https://tv.naver.com/1
 
1.4%
https://tv.kakao.com/top1
 
1.4%
Other values (5)5
 
6.8%
(Missing)24
32.4%

Length

2022-09-05T21:50:47.691753image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.youtube.com13
26.0%
https://v.qq.com9
18.0%
https://www.iq.com8
16.0%
https://dr.dk/drtv6
12.0%
https://www.bbc.co.uk/iplayer4
 
8.0%
https://the-hole.tv1
 
2.0%
https://hd.kinopoisk.ru1
 
2.0%
https://www.seezntv.com1
 
2.0%
https://tv.naver.com1
 
2.0%
https://tv.kakao.com/top1
 
2.0%
Other values (5)5
 
10.0%

Most occurring characters

ValueCountFrequency (%)
/138
12.9%
t130
12.1%
.98
 
9.2%
w91
 
8.5%
o61
 
5.7%
p59
 
5.5%
s56
 
5.2%
h55
 
5.1%
:50
 
4.7%
c46
 
4.3%
Other values (18)287
26.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter784
73.2%
Other Punctuation286
 
26.7%
Dash Punctuation1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t130
16.6%
w91
11.6%
o61
 
7.8%
p59
 
7.5%
s56
 
7.1%
h55
 
7.0%
c46
 
5.9%
m36
 
4.6%
u34
 
4.3%
q26
 
3.3%
Other values (14)190
24.2%
Other Punctuation
ValueCountFrequency (%)
/138
48.3%
.98
34.3%
:50
 
17.5%
Dash Punctuation
ValueCountFrequency (%)
-1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin784
73.2%
Common287
 
26.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
t130
16.6%
w91
11.6%
o61
 
7.8%
p59
 
7.5%
s56
 
7.1%
h55
 
7.0%
c46
 
5.9%
m36
 
4.6%
u34
 
4.3%
q26
 
3.3%
Other values (14)190
24.2%
Common
ValueCountFrequency (%)
/138
48.1%
.98
34.1%
:50
 
17.4%
-1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII1071
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/138
12.9%
t130
12.1%
.98
 
9.2%
w91
 
8.5%
o61
 
5.7%
p59
 
5.5%
s56
 
5.2%
h55
 
5.1%
:50
 
4.7%
c46
 
4.3%
Other values (18)287
26.8%

_embedded.show.dvdCountry
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing74
Missing (%)100.0%
Memory size720.0 B

_embedded.show.externals.tvrage
Categorical

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing73
Missing (%)98.6%
Memory size720.0 B
19056.0

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters7
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row19056.0

Common Values

ValueCountFrequency (%)
19056.01
 
1.4%
(Missing)73
98.6%

Length

2022-09-05T21:50:47.800149image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:50:47.884484image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
19056.01
100.0%

Most occurring characters

ValueCountFrequency (%)
02
28.6%
11
14.3%
91
14.3%
51
14.3%
61
14.3%
.1
14.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number6
85.7%
Other Punctuation1
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
02
33.3%
11
16.7%
91
16.7%
51
16.7%
61
16.7%
Other Punctuation
ValueCountFrequency (%)
.1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common7
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
02
28.6%
11
14.3%
91
14.3%
51
14.3%
61
14.3%
.1
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII7
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
02
28.6%
11
14.3%
91
14.3%
51
14.3%
61
14.3%
.1
14.3%

_embedded.show.externals.thetvdb
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct32
Distinct (%)72.7%
Missing30
Missing (%)40.5%
Infinite0
Infinite (%)0.0%
Mean362680.3182
Minimum104271
Maximum395145
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size720.0 B
2022-09-05T21:50:47.965363image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum104271
5-th percentile266573.9
Q1360222
median392214
Q3394120.5
95-th percentile394332
Maximum395145
Range290874
Interquartile range (IQR)33898.5

Descriptive statistics

Standard deviation57256.69026
Coefficient of variation (CV)0.1578709607
Kurtosis8.921810793
Mean362680.3182
Median Absolute Deviation (MAD)2262
Skewness-2.709142974
Sum15957934
Variance3278328580
MonotonicityNot monotonic
2022-09-05T21:50:48.078190image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
3943327
 
9.5%
3942212
 
2.7%
3922142
 
2.7%
3602222
 
2.7%
3933812
 
2.7%
2787932
 
2.7%
3940712
 
2.7%
3931741
 
1.4%
3946201
 
1.4%
3938441
 
1.4%
Other values (22)22
29.7%
(Missing)30
40.5%
ValueCountFrequency (%)
1042711
1.4%
2604361
1.4%
2651931
1.4%
2743991
1.4%
2787932
2.7%
2840461
1.4%
3346191
1.4%
3476401
1.4%
3524401
1.4%
3602222
2.7%
ValueCountFrequency (%)
3951451
 
1.4%
3946201
 
1.4%
3943327
9.5%
3942212
 
2.7%
3940871
 
1.4%
3940712
 
2.7%
3940451
 
1.4%
3938441
 
1.4%
3933812
 
2.7%
3931741
 
1.4%

_embedded.show.externals.imdb
Categorical

HIGH CORRELATION
MISSING

Distinct19
Distinct (%)65.5%
Missing45
Missing (%)60.8%
Memory size720.0 B
tt13439476
tt11939550
tt12940428
tt1714810
tt13598988
Other values (14)
14 

Length

Max length10
Median length10
Mean length9.724137931
Min length9

Characters and Unicode

Total characters282
Distinct characters11
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)48.3%

Sample

1st rowtt13423446
2nd rowtt11939550
3rd rowtt11939550
4th rowtt15127174
5th rowtt13439476

Common Values

ValueCountFrequency (%)
tt134394767
 
9.5%
tt119395502
 
2.7%
tt129404282
 
2.7%
tt17148102
 
2.7%
tt135989882
 
2.7%
tt110924821
 
1.4%
tt106806141
 
1.4%
tt35893121
 
1.4%
tt124579461
 
1.4%
tt155295661
 
1.4%
Other values (9)9
 
12.2%
(Missing)45
60.8%

Length

2022-09-05T21:50:48.185584image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
tt134394767
24.1%
tt129404282
 
6.9%
tt17148102
 
6.9%
tt135989882
 
6.9%
tt119395502
 
6.9%
tt122398241
 
3.4%
tt151271741
 
3.4%
tt49071781
 
3.4%
tt26102601
 
3.4%
tt73110101
 
3.4%
Other values (9)9
31.0%

Most occurring characters

ValueCountFrequency (%)
t58
20.6%
140
14.2%
432
11.3%
927
9.6%
324
8.5%
718
 
6.4%
018
 
6.4%
218
 
6.4%
817
 
6.0%
616
 
5.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number224
79.4%
Lowercase Letter58
 
20.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
140
17.9%
432
14.3%
927
12.1%
324
10.7%
718
8.0%
018
8.0%
218
8.0%
817
7.6%
616
 
7.1%
514
 
6.2%
Lowercase Letter
ValueCountFrequency (%)
t58
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common224
79.4%
Latin58
 
20.6%

Most frequent character per script

Common
ValueCountFrequency (%)
140
17.9%
432
14.3%
927
12.1%
324
10.7%
718
8.0%
018
8.0%
218
8.0%
817
7.6%
616
 
7.1%
514
 
6.2%
Latin
ValueCountFrequency (%)
t58
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII282
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t58
20.6%
140
14.2%
432
11.3%
927
9.6%
324
8.5%
718
 
6.4%
018
 
6.4%
218
 
6.4%
817
 
6.0%
616
 
5.7%

_embedded.show.image.medium
Categorical

HIGH CORRELATION
MISSING

Distinct47
Distinct (%)70.1%
Missing7
Missing (%)9.5%
Memory size720.0 B
https://static.tvmaze.com/uploads/images/medium_portrait/291/728871.jpg
https://static.tvmaze.com/uploads/images/medium_portrait/290/727385.jpg
 
4
https://static.tvmaze.com/uploads/images/medium_portrait/291/727584.jpg
 
4
https://static.tvmaze.com/uploads/images/medium_portrait/292/731984.jpg
 
2
https://static.tvmaze.com/uploads/images/medium_portrait/189/473411.jpg
 
2
Other values (42)
48 

Length

Max length72
Median length71
Mean length70.97014925
Min length70

Characters and Unicode

Total characters4755
Distinct characters32
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)53.7%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/medium_portrait/277/693293.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/medium_portrait/419/1048239.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/medium_portrait/379/948045.jpg
4th rowhttps://static.tvmaze.com/uploads/images/medium_portrait/278/696645.jpg
5th rowhttps://static.tvmaze.com/uploads/images/medium_portrait/299/748854.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_portrait/291/728871.jpg7
 
9.5%
https://static.tvmaze.com/uploads/images/medium_portrait/290/727385.jpg4
 
5.4%
https://static.tvmaze.com/uploads/images/medium_portrait/291/727584.jpg4
 
5.4%
https://static.tvmaze.com/uploads/images/medium_portrait/292/731984.jpg2
 
2.7%
https://static.tvmaze.com/uploads/images/medium_portrait/189/473411.jpg2
 
2.7%
https://static.tvmaze.com/uploads/images/medium_portrait/285/713040.jpg2
 
2.7%
https://static.tvmaze.com/uploads/images/medium_portrait/291/729467.jpg2
 
2.7%
https://static.tvmaze.com/uploads/images/medium_portrait/288/721432.jpg2
 
2.7%
https://static.tvmaze.com/uploads/images/medium_portrait/51/129595.jpg2
 
2.7%
https://static.tvmaze.com/uploads/images/medium_portrait/289/723488.jpg2
 
2.7%
Other values (37)38
51.4%
(Missing)7
 
9.5%

Length

2022-09-05T21:50:48.292385image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_portrait/291/728871.jpg7
 
10.4%
https://static.tvmaze.com/uploads/images/medium_portrait/291/727584.jpg4
 
6.0%
https://static.tvmaze.com/uploads/images/medium_portrait/290/727385.jpg4
 
6.0%
https://static.tvmaze.com/uploads/images/medium_portrait/288/721432.jpg2
 
3.0%
https://static.tvmaze.com/uploads/images/medium_portrait/337/844624.jpg2
 
3.0%
https://static.tvmaze.com/uploads/images/medium_portrait/51/129595.jpg2
 
3.0%
https://static.tvmaze.com/uploads/images/medium_portrait/289/723488.jpg2
 
3.0%
https://static.tvmaze.com/uploads/images/medium_portrait/291/729467.jpg2
 
3.0%
https://static.tvmaze.com/uploads/images/medium_portrait/285/713040.jpg2
 
3.0%
https://static.tvmaze.com/uploads/images/medium_portrait/189/473411.jpg2
 
3.0%
Other values (37)38
56.7%

Most occurring characters

ValueCountFrequency (%)
t469
 
9.9%
/469
 
9.9%
m335
 
7.0%
a335
 
7.0%
p268
 
5.6%
s268
 
5.6%
i268
 
5.6%
o201
 
4.2%
.201
 
4.2%
e201
 
4.2%
Other values (22)1740
36.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter3350
70.5%
Other Punctuation737
 
15.5%
Decimal Number601
 
12.6%
Connector Punctuation67
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t469
14.0%
m335
10.0%
a335
10.0%
p268
 
8.0%
s268
 
8.0%
i268
 
8.0%
o201
 
6.0%
e201
 
6.0%
u134
 
4.0%
r134
 
4.0%
Other values (8)737
22.0%
Decimal Number
ValueCountFrequency (%)
292
15.3%
783
13.8%
874
12.3%
968
11.3%
164
10.6%
360
10.0%
551
8.5%
451
8.5%
030
 
5.0%
628
 
4.7%
Other Punctuation
ValueCountFrequency (%)
/469
63.6%
.201
27.3%
:67
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_67
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin3350
70.5%
Common1405
29.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
t469
14.0%
m335
10.0%
a335
10.0%
p268
 
8.0%
s268
 
8.0%
i268
 
8.0%
o201
 
6.0%
e201
 
6.0%
u134
 
4.0%
r134
 
4.0%
Other values (8)737
22.0%
Common
ValueCountFrequency (%)
/469
33.4%
.201
14.3%
292
 
6.5%
783
 
5.9%
874
 
5.3%
968
 
4.8%
_67
 
4.8%
:67
 
4.8%
164
 
4.6%
360
 
4.3%
Other values (4)160
 
11.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII4755
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t469
 
9.9%
/469
 
9.9%
m335
 
7.0%
a335
 
7.0%
p268
 
5.6%
s268
 
5.6%
i268
 
5.6%
o201
 
4.2%
.201
 
4.2%
e201
 
4.2%
Other values (22)1740
36.6%

_embedded.show.image.original
Categorical

HIGH CORRELATION
MISSING

Distinct47
Distinct (%)70.1%
Missing7
Missing (%)9.5%
Memory size720.0 B
https://static.tvmaze.com/uploads/images/original_untouched/291/728871.jpg
https://static.tvmaze.com/uploads/images/original_untouched/290/727385.jpg
 
4
https://static.tvmaze.com/uploads/images/original_untouched/291/727584.jpg
 
4
https://static.tvmaze.com/uploads/images/original_untouched/292/731984.jpg
 
2
https://static.tvmaze.com/uploads/images/original_untouched/189/473411.jpg
 
2
Other values (42)
48 

Length

Max length75
Median length74
Mean length73.97014925
Min length73

Characters and Unicode

Total characters4956
Distinct characters33
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)53.7%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/original_untouched/277/693293.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/original_untouched/419/1048239.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/original_untouched/379/948045.jpg
4th rowhttps://static.tvmaze.com/uploads/images/original_untouched/278/696645.jpg
5th rowhttps://static.tvmaze.com/uploads/images/original_untouched/299/748854.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/291/728871.jpg7
 
9.5%
https://static.tvmaze.com/uploads/images/original_untouched/290/727385.jpg4
 
5.4%
https://static.tvmaze.com/uploads/images/original_untouched/291/727584.jpg4
 
5.4%
https://static.tvmaze.com/uploads/images/original_untouched/292/731984.jpg2
 
2.7%
https://static.tvmaze.com/uploads/images/original_untouched/189/473411.jpg2
 
2.7%
https://static.tvmaze.com/uploads/images/original_untouched/285/713040.jpg2
 
2.7%
https://static.tvmaze.com/uploads/images/original_untouched/291/729467.jpg2
 
2.7%
https://static.tvmaze.com/uploads/images/original_untouched/288/721432.jpg2
 
2.7%
https://static.tvmaze.com/uploads/images/original_untouched/51/129595.jpg2
 
2.7%
https://static.tvmaze.com/uploads/images/original_untouched/289/723488.jpg2
 
2.7%
Other values (37)38
51.4%
(Missing)7
 
9.5%

Length

2022-09-05T21:50:48.407130image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/291/728871.jpg7
 
10.4%
https://static.tvmaze.com/uploads/images/original_untouched/291/727584.jpg4
 
6.0%
https://static.tvmaze.com/uploads/images/original_untouched/290/727385.jpg4
 
6.0%
https://static.tvmaze.com/uploads/images/original_untouched/288/721432.jpg2
 
3.0%
https://static.tvmaze.com/uploads/images/original_untouched/337/844624.jpg2
 
3.0%
https://static.tvmaze.com/uploads/images/original_untouched/51/129595.jpg2
 
3.0%
https://static.tvmaze.com/uploads/images/original_untouched/289/723488.jpg2
 
3.0%
https://static.tvmaze.com/uploads/images/original_untouched/291/729467.jpg2
 
3.0%
https://static.tvmaze.com/uploads/images/original_untouched/285/713040.jpg2
 
3.0%
https://static.tvmaze.com/uploads/images/original_untouched/189/473411.jpg2
 
3.0%
Other values (37)38
56.7%

Most occurring characters

ValueCountFrequency (%)
/469
 
9.5%
t402
 
8.1%
a335
 
6.8%
s268
 
5.4%
i268
 
5.4%
o268
 
5.4%
p201
 
4.1%
c201
 
4.1%
.201
 
4.1%
g201
 
4.1%
Other values (23)2142
43.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter3551
71.7%
Other Punctuation737
 
14.9%
Decimal Number601
 
12.1%
Connector Punctuation67
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t402
 
11.3%
a335
 
9.4%
s268
 
7.5%
i268
 
7.5%
o268
 
7.5%
p201
 
5.7%
c201
 
5.7%
g201
 
5.7%
m201
 
5.7%
e201
 
5.7%
Other values (9)1005
28.3%
Decimal Number
ValueCountFrequency (%)
292
15.3%
783
13.8%
874
12.3%
968
11.3%
164
10.6%
360
10.0%
551
8.5%
451
8.5%
030
 
5.0%
628
 
4.7%
Other Punctuation
ValueCountFrequency (%)
/469
63.6%
.201
27.3%
:67
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_67
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin3551
71.7%
Common1405
 
28.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
t402
 
11.3%
a335
 
9.4%
s268
 
7.5%
i268
 
7.5%
o268
 
7.5%
p201
 
5.7%
c201
 
5.7%
g201
 
5.7%
m201
 
5.7%
e201
 
5.7%
Other values (9)1005
28.3%
Common
ValueCountFrequency (%)
/469
33.4%
.201
14.3%
292
 
6.5%
783
 
5.9%
874
 
5.3%
968
 
4.8%
:67
 
4.8%
_67
 
4.8%
164
 
4.6%
360
 
4.3%
Other values (4)160
 
11.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII4956
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/469
 
9.5%
t402
 
8.1%
a335
 
6.8%
s268
 
5.4%
i268
 
5.4%
o268
 
5.4%
p201
 
4.1%
c201
 
4.1%
.201
 
4.1%
g201
 
4.1%
Other values (23)2142
43.2%

_embedded.show.summary
Categorical

HIGH CORRELATION
MISSING

Distinct45
Distinct (%)64.3%
Missing4
Missing (%)5.4%
Memory size720.0 B
<p>In a kingdom dominated by men, it is the ultimate battle of the sexes to win the war being waged against gender equality. Every character is grey and they must fight for what they believe is right in order to survive in Paurashpur.</p>
<p>Becoming parents to triplets is a big life change and a marathon of a parenting task, which puts both family and parents under pressure.</p>
<p>The play is set in the turbulent period of the Republic of China in Shanghai. In a turbulent era, the forensic doctor Che Suwei and the gentleman detective Gu Yuan are intertwined with various forces. "Deputy Inspector Kang Yichen, and the innocent and lively reporter Cao Qingluo worked together to crack out a number of weird and curious cases, and restore the truth.</p>
 
4
<p>The world of celebrity has been transformed since the turn of the century, driven by some of the most dramatic technological and cultural developments in recent times.</p><p>This series charting the explosion in celebrity culture.</p>
 
4
<p>Lin Luo Jing accidentally gets drawn into a game world where she is the daughter of the prime minister and meets all kind of beautiful men with different personalities. Among them are a sword deity, an imperial bodyguard, a playful rich man and an arrogant prince. The system informs her that she can only return to the real world after she finds her true love. While there seems tobe an abundance of good men around Luo Jing, there is one man she can't stand at all: the prince of the barbarian Yuan Kingdom Zhong Wu Mei. But out of all men, she ends up in an arranged marriage with Wu Mei.</p><p>Thus begins their love-hate relationship and her journey to find true love in order to win the game.</p>
 
2
Other values (40)
47 

Length

Max length1483
Median length446.5
Mean length330.6285714
Min length39

Characters and Unicode

Total characters23144
Distinct characters115
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33 ?
Unique (%)47.1%

Sample

1st row<p>Solo performances of stand-up comedians from the underground and popular TV and Internet projects. Each new release is a new concert with its own atmosphere and humor.</p>
2nd row<p>Юмористическое шоу, где знания участников так же важны, как и юмор! Игра состоит из трех раундов. Ведущий зачитывает начало цитаты, стихотворения или факта, а конкурсант должен закончить их либо смешно, либо правильно! Победит тот, кто окажется самым умным и веселым!</p>
3rd row<p>Russian music artists reveal themselves from unexpected sides in the Anton Belyaev's show.</p>
4th row<p>The power of beginnings, the energy of the core stone; one may find it good, one may find it evil. During a normal investigation, Yue Juntian finds himself drawn into the battle between the 'beginnings' of Yun City; Jiang Xin arrives in Yun City to stop Li Zunyuan's plan to take over. The two influence each other - one solves the mystery of their birth, the other redeems themselves. Together, they oppose Li Zunyuan.<br /> </p>
5th row<p>The protagonist Qin Chen, who was originally the top genius in the military domain, was conspired by the people to fall into the death canyon in the forbidden land of the mainland. Qin Chen, who was inevitably dead, unexpectedly triggered the power of the mysterious ancient sword.<br /><br />Three hundred years later, in a remote part of the Tianwu mainland, a boy of the same name accidentally inherited Qin Chen's will. As the beloved grandson of King Dingwu of the Daqi National Army, due to the birth father's birth, the mother and son were treated coldly in Dingwu's palace and lived together. In order to rewrite the myth of the strong man in hope of the sun, and to protect everything he loves, Qin Chen resolutely took up the responsibility of maintaining the five kingdoms of the world and set foot on the road of martial arts again.</p>

Common Values

ValueCountFrequency (%)
<p>In a kingdom dominated by men, it is the ultimate battle of the sexes to win the war being waged against gender equality. Every character is grey and they must fight for what they believe is right in order to survive in Paurashpur.</p>7
 
9.5%
<p>Becoming parents to triplets is a big life change and a marathon of a parenting task, which puts both family and parents under pressure.</p>6
 
8.1%
<p>The play is set in the turbulent period of the Republic of China in Shanghai. In a turbulent era, the forensic doctor Che Suwei and the gentleman detective Gu Yuan are intertwined with various forces. "Deputy Inspector Kang Yichen, and the innocent and lively reporter Cao Qingluo worked together to crack out a number of weird and curious cases, and restore the truth.</p>4
 
5.4%
<p>The world of celebrity has been transformed since the turn of the century, driven by some of the most dramatic technological and cultural developments in recent times.</p><p>This series charting the explosion in celebrity culture.</p>4
 
5.4%
<p>Lin Luo Jing accidentally gets drawn into a game world where she is the daughter of the prime minister and meets all kind of beautiful men with different personalities. Among them are a sword deity, an imperial bodyguard, a playful rich man and an arrogant prince. The system informs her that she can only return to the real world after she finds her true love. While there seems tobe an abundance of good men around Luo Jing, there is one man she can't stand at all: the prince of the barbarian Yuan Kingdom Zhong Wu Mei. But out of all men, she ends up in an arranged marriage with Wu Mei.</p><p>Thus begins their love-hate relationship and her journey to find true love in order to win the game.</p>2
 
2.7%
<p>During the Yin Dynasty, Dong Yue, a brave general in the Dingyuan Rebellion, was sent back in time to stop a war that would claim the lives of countless innocents. She sets out to murder corrupted officer Lu Yuantong in an attempt to prevent war, and during her journey she met Feng Xi and Pang Yu. Pang Yu and Feng Xi were old friends who cared deeply for each other, but fell out and turn into enemies. While trying to reconcile the two brothers, Dong Yue also tries to stop Lu Yuantang's evil schemes which are poised to tear the nation apart with their help.</p>2
 
2.7%
<p>Lin Luojing enters the XR system due to a technology competition, and time-travels to the Sheng Yuan Dynasty of the game. To return back to reality, she has to find her true love and max the "favorability points". In the midst of exchanging tactics with arrogant prince Zhong Wu Mei, her former personal guard Liu Xiu Wen returns to the capital, this time with a new identity as the Persian Prince. Liu Xiu Wen vows to wage war on Zhong Wuyan. Facing both internal and external crises and conflicts, how will Lin Luojing resolve it and embark on her journey back home?</p>2
 
2.7%
<p>Two unlikely individuals join forces to find the truth behind a series of murders using an unconventional method. Chen Si, a female detective with a sense of justice, unexpectedly becomess partners with Yuan Shuai, a dream interpreter with a dark past.</p>2
 
2.7%
<p>A daring, funny, and brutally honest show that covers politics, entertainment, movies, sports, and pop culture.</p>2
 
2.7%
<p>A story that follows two people's brave pursuit of love from their campus days to their humble beginnings as they enter the workplace to chase after their dreams together.</p>2
 
2.7%
Other values (35)37
50.0%
(Missing)4
 
5.4%

Length

2022-09-05T21:50:48.532975image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the248
 
6.4%
and153
 
4.0%
of118
 
3.1%
to112
 
2.9%
a104
 
2.7%
in89
 
2.3%
is59
 
1.5%
with48
 
1.2%
her38
 
1.0%
they29
 
0.7%
Other values (1176)2870
74.2%

Most occurring characters

ValueCountFrequency (%)
3790
16.4%
e2259
 
9.8%
t1580
 
6.8%
n1377
 
5.9%
a1361
 
5.9%
i1263
 
5.5%
o1203
 
5.2%
r1183
 
5.1%
s1023
 
4.4%
h915
 
4.0%
Other values (105)7190
31.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter17660
76.3%
Space Separator3798
 
16.4%
Uppercase Letter651
 
2.8%
Other Punctuation573
 
2.5%
Math Symbol398
 
1.7%
Dash Punctuation38
 
0.2%
Decimal Number22
 
0.1%
Open Punctuation2
 
< 0.1%
Close Punctuation2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e2259
12.8%
t1580
 
8.9%
n1377
 
7.8%
a1361
 
7.7%
i1263
 
7.2%
o1203
 
6.8%
r1183
 
6.7%
s1023
 
5.8%
h915
 
5.2%
l642
 
3.6%
Other values (48)4854
27.5%
Uppercase Letter
ValueCountFrequency (%)
T81
 
12.4%
S69
 
10.6%
A42
 
6.5%
Y39
 
6.0%
L35
 
5.4%
W33
 
5.1%
I32
 
4.9%
D32
 
4.9%
C30
 
4.6%
H26
 
4.0%
Other values (20)232
35.6%
Other Punctuation
ValueCountFrequency (%)
,212
37.0%
.193
33.7%
/102
17.8%
'30
 
5.2%
"12
 
2.1%
!11
 
1.9%
:6
 
1.0%
?3
 
0.5%
2
 
0.3%
;2
 
0.3%
Decimal Number
ValueCountFrequency (%)
26
27.3%
04
18.2%
14
18.2%
53
13.6%
72
 
9.1%
31
 
4.5%
41
 
4.5%
81
 
4.5%
Dash Punctuation
ValueCountFrequency (%)
-30
78.9%
7
 
18.4%
1
 
2.6%
Space Separator
ValueCountFrequency (%)
3790
99.8%
 8
 
0.2%
Math Symbol
ValueCountFrequency (%)
>199
50.0%
<199
50.0%
Open Punctuation
ValueCountFrequency (%)
(2
100.0%
Close Punctuation
ValueCountFrequency (%)
)2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin18093
78.2%
Common4833
 
20.9%
Cyrillic218
 
0.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e2259
12.5%
t1580
 
8.7%
n1377
 
7.6%
a1361
 
7.5%
i1263
 
7.0%
o1203
 
6.6%
r1183
 
6.5%
s1023
 
5.7%
h915
 
5.1%
l642
 
3.5%
Other values (44)5287
29.2%
Cyrillic
ValueCountFrequency (%)
о22
 
10.1%
и21
 
9.6%
а20
 
9.2%
т20
 
9.2%
н14
 
6.4%
е14
 
6.4%
с11
 
5.0%
к11
 
5.0%
р8
 
3.7%
м8
 
3.7%
Other values (24)69
31.7%
Common
ValueCountFrequency (%)
3790
78.4%
,212
 
4.4%
>199
 
4.1%
<199
 
4.1%
.193
 
4.0%
/102
 
2.1%
'30
 
0.6%
-30
 
0.6%
"12
 
0.2%
!11
 
0.2%
Other values (17)55
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII22905
99.0%
Cyrillic218
 
0.9%
None11
 
< 0.1%
Punctuation10
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3790
16.5%
e2259
 
9.9%
t1580
 
6.9%
n1377
 
6.0%
a1361
 
5.9%
i1263
 
5.5%
o1203
 
5.3%
r1183
 
5.2%
s1023
 
4.5%
h915
 
4.0%
Other values (65)6951
30.3%
Cyrillic
ValueCountFrequency (%)
о22
 
10.1%
и21
 
9.6%
а20
 
9.2%
т20
 
9.2%
н14
 
6.4%
е14
 
6.4%
с11
 
5.0%
к11
 
5.0%
р8
 
3.7%
м8
 
3.7%
Other values (24)69
31.7%
None
ValueCountFrequency (%)
 8
72.7%
ó2
 
18.2%
å1
 
9.1%
Punctuation
ValueCountFrequency (%)
7
70.0%
2
 
20.0%
1
 
10.0%

_embedded.show.updated
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct49
Distinct (%)66.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1634467752
Minimum1604587119
Maximum1662346277
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size720.0 B
2022-09-05T21:50:48.651432image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1604587119
5-th percentile1609140039
Q11612569254
median1641821222
Q31654382071
95-th percentile1661874261
Maximum1662346277
Range57759158
Interquartile range (IQR)41812816.5

Descriptive statistics

Standard deviation20614914.7
Coefficient of variation (CV)0.01261261635
Kurtosis-1.760250412
Mean1634467752
Median Absolute Deviation (MAD)20056102.5
Skewness-0.04055129778
Sum1.209506136 × 1011
Variance4.24974708 × 1014
MonotonicityNot monotonic
2022-09-05T21:50:48.771839image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
16098001057
 
9.5%
16193750216
 
8.1%
16549760864
 
5.4%
16113552204
 
5.4%
16549766662
 
2.7%
16095351412
 
2.7%
16543820712
 
2.7%
16128425832
 
2.7%
16602618862
 
2.7%
16124781452
 
2.7%
Other values (39)41
55.4%
ValueCountFrequency (%)
16045871191
 
1.4%
16078871751
 
1.4%
16083529671
 
1.4%
16084062791
 
1.4%
16095351412
 
2.7%
16098001057
9.5%
16113552204
5.4%
16124781452
 
2.7%
16128425832
 
2.7%
16129809601
 
1.4%
ValueCountFrequency (%)
16623462771
1.4%
16619744211
1.4%
16619689571
1.4%
16618875351
1.4%
16618671131
1.4%
16614348681
1.4%
16610141231
1.4%
16610084771
1.4%
16602618862
2.7%
16559117751
1.4%

_embedded.show._links.self.href
Categorical

HIGH CORRELATION

Distinct49
Distinct (%)66.2%
Missing0
Missing (%)0.0%
Memory size720.0 B
https://api.tvmaze.com/shows/52736
https://api.tvmaze.com/shows/54955
https://api.tvmaze.com/shows/52655
 
4
https://api.tvmaze.com/shows/52661
 
4
https://api.tvmaze.com/shows/52936
 
2
Other values (44)
51 

Length

Max length34
Median length34
Mean length33.98648649
Min length33

Characters and Unicode

Total characters2515
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique37 ?
Unique (%)50.0%

Sample

1st rowhttps://api.tvmaze.com/shows/51065
2nd rowhttps://api.tvmaze.com/shows/52044
3rd rowhttps://api.tvmaze.com/shows/52933
4th rowhttps://api.tvmaze.com/shows/51336
5th rowhttps://api.tvmaze.com/shows/54033

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/shows/527367
 
9.5%
https://api.tvmaze.com/shows/549556
 
8.1%
https://api.tvmaze.com/shows/526554
 
5.4%
https://api.tvmaze.com/shows/526614
 
5.4%
https://api.tvmaze.com/shows/529362
 
2.7%
https://api.tvmaze.com/shows/521042
 
2.7%
https://api.tvmaze.com/shows/414902
 
2.7%
https://api.tvmaze.com/shows/524002
 
2.7%
https://api.tvmaze.com/shows/527842
 
2.7%
https://api.tvmaze.com/shows/525242
 
2.7%
Other values (39)41
55.4%

Length

2022-09-05T21:50:48.884474image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/shows/527367
 
9.5%
https://api.tvmaze.com/shows/549556
 
8.1%
https://api.tvmaze.com/shows/526554
 
5.4%
https://api.tvmaze.com/shows/526614
 
5.4%
https://api.tvmaze.com/shows/527842
 
2.7%
https://api.tvmaze.com/shows/562882
 
2.7%
https://api.tvmaze.com/shows/525242
 
2.7%
https://api.tvmaze.com/shows/152502
 
2.7%
https://api.tvmaze.com/shows/524002
 
2.7%
https://api.tvmaze.com/shows/414902
 
2.7%
Other values (39)41
55.4%

Most occurring characters

ValueCountFrequency (%)
/296
 
11.8%
s222
 
8.8%
t222
 
8.8%
h148
 
5.9%
p148
 
5.9%
a148
 
5.9%
.148
 
5.9%
o148
 
5.9%
m148
 
5.9%
587
 
3.5%
Other values (16)800
31.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1628
64.7%
Other Punctuation518
 
20.6%
Decimal Number369
 
14.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s222
13.6%
t222
13.6%
h148
9.1%
p148
9.1%
a148
9.1%
o148
9.1%
m148
9.1%
e74
 
4.5%
w74
 
4.5%
c74
 
4.5%
Other values (3)222
13.6%
Decimal Number
ValueCountFrequency (%)
587
23.6%
249
13.3%
443
11.7%
639
10.6%
338
10.3%
026
 
7.0%
125
 
6.8%
924
 
6.5%
721
 
5.7%
817
 
4.6%
Other Punctuation
ValueCountFrequency (%)
/296
57.1%
.148
28.6%
:74
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin1628
64.7%
Common887
35.3%

Most frequent character per script

Common
ValueCountFrequency (%)
/296
33.4%
.148
16.7%
587
 
9.8%
:74
 
8.3%
249
 
5.5%
443
 
4.8%
639
 
4.4%
338
 
4.3%
026
 
2.9%
125
 
2.8%
Other values (3)62
 
7.0%
Latin
ValueCountFrequency (%)
s222
13.6%
t222
13.6%
h148
9.1%
p148
9.1%
a148
9.1%
o148
9.1%
m148
9.1%
e74
 
4.5%
w74
 
4.5%
c74
 
4.5%
Other values (3)222
13.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII2515
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/296
 
11.8%
s222
 
8.8%
t222
 
8.8%
h148
 
5.9%
p148
 
5.9%
a148
 
5.9%
.148
 
5.9%
o148
 
5.9%
m148
 
5.9%
587
 
3.5%
Other values (16)800
31.8%
Distinct49
Distinct (%)66.2%
Missing0
Missing (%)0.0%
Memory size720.0 B
https://api.tvmaze.com/episodes/1997187
https://api.tvmaze.com/episodes/2077453
https://api.tvmaze.com/episodes/2340036
 
4
https://api.tvmaze.com/episodes/1994079
 
4
https://api.tvmaze.com/episodes/2007724
 
2
Other values (44)
51 

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters2886
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique37 ?
Unique (%)50.0%

Sample

1st rowhttps://api.tvmaze.com/episodes/2007760
2nd rowhttps://api.tvmaze.com/episodes/2376787
3rd rowhttps://api.tvmaze.com/episodes/2245512
4th rowhttps://api.tvmaze.com/episodes/1964569
5th rowhttps://api.tvmaze.com/episodes/2309442

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/episodes/19971877
 
9.5%
https://api.tvmaze.com/episodes/20774536
 
8.1%
https://api.tvmaze.com/episodes/23400364
 
5.4%
https://api.tvmaze.com/episodes/19940794
 
5.4%
https://api.tvmaze.com/episodes/20077242
 
2.7%
https://api.tvmaze.com/episodes/19760542
 
2.7%
https://api.tvmaze.com/episodes/23244402
 
2.7%
https://api.tvmaze.com/episodes/19849632
 
2.7%
https://api.tvmaze.com/episodes/19986262
 
2.7%
https://api.tvmaze.com/episodes/19880792
 
2.7%
Other values (39)41
55.4%

Length

2022-09-05T21:50:48.983547image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/19971877
 
9.5%
https://api.tvmaze.com/episodes/20774536
 
8.1%
https://api.tvmaze.com/episodes/23400364
 
5.4%
https://api.tvmaze.com/episodes/19940794
 
5.4%
https://api.tvmaze.com/episodes/19986262
 
2.7%
https://api.tvmaze.com/episodes/21264902
 
2.7%
https://api.tvmaze.com/episodes/19880792
 
2.7%
https://api.tvmaze.com/episodes/23012762
 
2.7%
https://api.tvmaze.com/episodes/19849632
 
2.7%
https://api.tvmaze.com/episodes/23244402
 
2.7%
Other values (39)41
55.4%

Most occurring characters

ValueCountFrequency (%)
/296
 
10.3%
p222
 
7.7%
s222
 
7.7%
e222
 
7.7%
t222
 
7.7%
o148
 
5.1%
a148
 
5.1%
i148
 
5.1%
.148
 
5.1%
m148
 
5.1%
Other values (16)962
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1850
64.1%
Other Punctuation518
 
17.9%
Decimal Number518
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
p222
12.0%
s222
12.0%
e222
12.0%
t222
12.0%
o148
8.0%
a148
8.0%
i148
8.0%
m148
8.0%
h74
 
4.0%
d74
 
4.0%
Other values (3)222
12.0%
Decimal Number
ValueCountFrequency (%)
280
15.4%
974
14.3%
760
11.6%
058
11.2%
150
9.7%
349
9.5%
448
9.3%
638
7.3%
832
 
6.2%
529
 
5.6%
Other Punctuation
ValueCountFrequency (%)
/296
57.1%
.148
28.6%
:74
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin1850
64.1%
Common1036
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
/296
28.6%
.148
14.3%
280
 
7.7%
974
 
7.1%
:74
 
7.1%
760
 
5.8%
058
 
5.6%
150
 
4.8%
349
 
4.7%
448
 
4.6%
Other values (3)99
 
9.6%
Latin
ValueCountFrequency (%)
p222
12.0%
s222
12.0%
e222
12.0%
t222
12.0%
o148
8.0%
a148
8.0%
i148
8.0%
m148
8.0%
h74
 
4.0%
d74
 
4.0%
Other values (3)222
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII2886
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/296
 
10.3%
p222
 
7.7%
s222
 
7.7%
e222
 
7.7%
t222
 
7.7%
o148
 
5.1%
a148
 
5.1%
i148
 
5.1%
.148
 
5.1%
m148
 
5.1%
Other values (16)962
33.3%

_embedded.show.webChannel.country.name
Categorical

HIGH CORRELATION
MISSING

Distinct12
Distinct (%)27.3%
Missing30
Missing (%)40.5%
Memory size720.0 B
China
12 
India
Denmark
United Kingdom
Korea, Republic of
Other values (7)
12 

Length

Max length25
Median length18
Mean length9.022727273
Min length5

Characters and Unicode

Total characters397
Distinct characters35
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)6.8%

Sample

1st rowRussian Federation
2nd rowRussian Federation
3rd rowChina
4th rowChina
5th rowKorea, Republic of

Common Values

ValueCountFrequency (%)
China12
 
16.2%
India7
 
9.5%
Denmark6
 
8.1%
United Kingdom4
 
5.4%
Korea, Republic of3
 
4.1%
Norway3
 
4.1%
Russian Federation2
 
2.7%
Poland2
 
2.7%
United States2
 
2.7%
Taiwan, Province of China1
 
1.4%
Other values (2)2
 
2.7%
(Missing)30
40.5%

Length

2022-09-05T21:50:49.086162image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
china13
20.3%
india7
10.9%
denmark6
9.4%
united6
9.4%
of5
 
7.8%
kingdom4
 
6.2%
republic4
 
6.2%
korea3
 
4.7%
norway3
 
4.7%
poland2
 
3.1%
Other values (8)11
17.2%

Most occurring characters

ValueCountFrequency (%)
n46
 
11.6%
a46
 
11.6%
i42
 
10.6%
e26
 
6.5%
d22
 
5.5%
o20
 
5.0%
20
 
5.0%
r16
 
4.0%
h14
 
3.5%
C13
 
3.3%
Other values (25)132
33.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter313
78.8%
Uppercase Letter59
 
14.9%
Space Separator20
 
5.0%
Other Punctuation5
 
1.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n46
14.7%
a46
14.7%
i42
13.4%
e26
8.3%
d22
 
7.0%
o20
 
6.4%
r16
 
5.1%
h14
 
4.5%
t12
 
3.8%
m11
 
3.5%
Other values (12)58
18.5%
Uppercase Letter
ValueCountFrequency (%)
C13
22.0%
I9
15.3%
K7
11.9%
U6
10.2%
D6
10.2%
R6
10.2%
N3
 
5.1%
P3
 
5.1%
F2
 
3.4%
S2
 
3.4%
Space Separator
ValueCountFrequency (%)
20
100.0%
Other Punctuation
ValueCountFrequency (%)
,5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin372
93.7%
Common25
 
6.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
n46
 
12.4%
a46
 
12.4%
i42
 
11.3%
e26
 
7.0%
d22
 
5.9%
o20
 
5.4%
r16
 
4.3%
h14
 
3.8%
C13
 
3.5%
t12
 
3.2%
Other values (23)115
30.9%
Common
ValueCountFrequency (%)
20
80.0%
,5
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII397
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n46
 
11.6%
a46
 
11.6%
i42
 
10.6%
e26
 
6.5%
d22
 
5.5%
o20
 
5.0%
20
 
5.0%
r16
 
4.0%
h14
 
3.5%
C13
 
3.3%
Other values (25)132
33.2%

_embedded.show.webChannel.country.code
Categorical

HIGH CORRELATION
MISSING

Distinct12
Distinct (%)27.3%
Missing30
Missing (%)40.5%
Memory size720.0 B
CN
12 
IN
DK
GB
KR
Other values (7)
12 

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters88
Distinct characters16
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)6.8%

Sample

1st rowRU
2nd rowRU
3rd rowCN
4th rowCN
5th rowKR

Common Values

ValueCountFrequency (%)
CN12
 
16.2%
IN7
 
9.5%
DK6
 
8.1%
GB4
 
5.4%
KR3
 
4.1%
NO3
 
4.1%
RU2
 
2.7%
PL2
 
2.7%
US2
 
2.7%
TW1
 
1.4%
Other values (2)2
 
2.7%
(Missing)30
40.5%

Length

2022-09-05T21:50:49.178909image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
cn12
27.3%
in7
15.9%
dk6
13.6%
gb4
 
9.1%
kr3
 
6.8%
no3
 
6.8%
ru2
 
4.5%
pl2
 
4.5%
us2
 
4.5%
tw1
 
2.3%
Other values (2)2
 
4.5%

Most occurring characters

ValueCountFrequency (%)
N22
25.0%
C12
13.6%
K9
10.2%
I8
 
9.1%
D6
 
6.8%
R6
 
6.8%
G4
 
4.5%
B4
 
4.5%
U4
 
4.5%
O3
 
3.4%
Other values (6)10
11.4%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter88
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N22
25.0%
C12
13.6%
K9
10.2%
I8
 
9.1%
D6
 
6.8%
R6
 
6.8%
G4
 
4.5%
B4
 
4.5%
U4
 
4.5%
O3
 
3.4%
Other values (6)10
11.4%

Most occurring scripts

ValueCountFrequency (%)
Latin88
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N22
25.0%
C12
13.6%
K9
10.2%
I8
 
9.1%
D6
 
6.8%
R6
 
6.8%
G4
 
4.5%
B4
 
4.5%
U4
 
4.5%
O3
 
3.4%
Other values (6)10
11.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII88
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N22
25.0%
C12
13.6%
K9
10.2%
I8
 
9.1%
D6
 
6.8%
R6
 
6.8%
G4
 
4.5%
B4
 
4.5%
U4
 
4.5%
O3
 
3.4%
Other values (6)10
11.4%

_embedded.show.webChannel.country.timezone
Categorical

HIGH CORRELATION
MISSING

Distinct12
Distinct (%)27.3%
Missing30
Missing (%)40.5%
Memory size720.0 B
Asia/Shanghai
12 
Asia/Kolkata
Europe/Copenhagen
Europe/London
Asia/Seoul
Other values (7)
12 

Length

Max length17
Median length16
Mean length13.11363636
Min length10

Characters and Unicode

Total characters577
Distinct characters32
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)6.8%

Sample

1st rowAsia/Kamchatka
2nd rowAsia/Kamchatka
3rd rowAsia/Shanghai
4th rowAsia/Shanghai
5th rowAsia/Seoul

Common Values

ValueCountFrequency (%)
Asia/Shanghai12
 
16.2%
Asia/Kolkata7
 
9.5%
Europe/Copenhagen6
 
8.1%
Europe/London4
 
5.4%
Asia/Seoul3
 
4.1%
Europe/Oslo3
 
4.1%
Asia/Kamchatka2
 
2.7%
Europe/Warsaw2
 
2.7%
America/New_York2
 
2.7%
Asia/Taipei1
 
1.4%
Other values (2)2
 
2.7%
(Missing)30
40.5%

Length

2022-09-05T21:50:49.271871image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
asia/shanghai12
27.3%
asia/kolkata7
15.9%
europe/copenhagen6
13.6%
europe/london4
 
9.1%
asia/seoul3
 
6.8%
europe/oslo3
 
6.8%
asia/kamchatka2
 
4.5%
europe/warsaw2
 
4.5%
america/new_york2
 
4.5%
asia/taipei1
 
2.3%
Other values (2)2
 
4.5%

Most occurring characters

ValueCountFrequency (%)
a86
14.9%
o45
 
7.8%
/44
 
7.6%
i43
 
7.5%
e36
 
6.2%
n34
 
5.9%
h33
 
5.7%
s32
 
5.5%
A29
 
5.0%
p22
 
3.8%
Other values (22)173
30.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter441
76.4%
Uppercase Letter90
 
15.6%
Other Punctuation44
 
7.6%
Connector Punctuation2
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a86
19.5%
o45
10.2%
i43
9.8%
e36
8.2%
n34
 
7.7%
h33
 
7.5%
s32
 
7.3%
p22
 
5.0%
r22
 
5.0%
g19
 
4.3%
Other values (8)69
15.6%
Uppercase Letter
ValueCountFrequency (%)
A29
32.2%
E15
16.7%
S15
16.7%
K9
 
10.0%
C6
 
6.7%
L4
 
4.4%
O3
 
3.3%
W2
 
2.2%
N2
 
2.2%
Y2
 
2.2%
Other values (2)3
 
3.3%
Other Punctuation
ValueCountFrequency (%)
/44
100.0%
Connector Punctuation
ValueCountFrequency (%)
_2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin531
92.0%
Common46
 
8.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
a86
16.2%
o45
 
8.5%
i43
 
8.1%
e36
 
6.8%
n34
 
6.4%
h33
 
6.2%
s32
 
6.0%
A29
 
5.5%
p22
 
4.1%
r22
 
4.1%
Other values (20)149
28.1%
Common
ValueCountFrequency (%)
/44
95.7%
_2
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII577
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a86
14.9%
o45
 
7.8%
/44
 
7.6%
i43
 
7.5%
e36
 
6.2%
n34
 
5.9%
h33
 
5.7%
s32
 
5.5%
A29
 
5.0%
p22
 
3.8%
Other values (22)173
30.0%

image.medium
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct12
Distinct (%)100.0%
Missing62
Missing (%)83.8%
Memory size720.0 B
https://static.tvmaze.com/uploads/images/medium_landscape/294/737210.jpg
https://static.tvmaze.com/uploads/images/medium_landscape/291/728291.jpg
https://static.tvmaze.com/uploads/images/medium_landscape/293/733849.jpg
https://static.tvmaze.com/uploads/images/medium_landscape/291/729339.jpg
https://static.tvmaze.com/uploads/images/medium_landscape/292/730358.jpg
Other values (7)

Length

Max length72
Median length72
Mean length72
Min length72

Characters and Unicode

Total characters864
Distinct characters32
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)100.0%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/medium_landscape/294/737210.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/medium_landscape/291/728291.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/medium_landscape/293/733849.jpg
4th rowhttps://static.tvmaze.com/uploads/images/medium_landscape/291/729339.jpg
5th rowhttps://static.tvmaze.com/uploads/images/medium_landscape/292/730358.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_landscape/294/737210.jpg1
 
1.4%
https://static.tvmaze.com/uploads/images/medium_landscape/291/728291.jpg1
 
1.4%
https://static.tvmaze.com/uploads/images/medium_landscape/293/733849.jpg1
 
1.4%
https://static.tvmaze.com/uploads/images/medium_landscape/291/729339.jpg1
 
1.4%
https://static.tvmaze.com/uploads/images/medium_landscape/292/730358.jpg1
 
1.4%
https://static.tvmaze.com/uploads/images/medium_landscape/291/728205.jpg1
 
1.4%
https://static.tvmaze.com/uploads/images/medium_landscape/289/724614.jpg1
 
1.4%
https://static.tvmaze.com/uploads/images/medium_landscape/291/727577.jpg1
 
1.4%
https://static.tvmaze.com/uploads/images/medium_landscape/291/727732.jpg1
 
1.4%
https://static.tvmaze.com/uploads/images/medium_landscape/291/727731.jpg1
 
1.4%
Other values (2)2
 
2.7%
(Missing)62
83.8%

Length

2022-09-05T21:50:49.360567image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_landscape/294/737210.jpg1
8.3%
https://static.tvmaze.com/uploads/images/medium_landscape/291/728291.jpg1
8.3%
https://static.tvmaze.com/uploads/images/medium_landscape/293/733849.jpg1
8.3%
https://static.tvmaze.com/uploads/images/medium_landscape/291/729339.jpg1
8.3%
https://static.tvmaze.com/uploads/images/medium_landscape/292/730358.jpg1
8.3%
https://static.tvmaze.com/uploads/images/medium_landscape/291/728205.jpg1
8.3%
https://static.tvmaze.com/uploads/images/medium_landscape/289/724614.jpg1
8.3%
https://static.tvmaze.com/uploads/images/medium_landscape/291/727577.jpg1
8.3%
https://static.tvmaze.com/uploads/images/medium_landscape/291/727732.jpg1
8.3%
https://static.tvmaze.com/uploads/images/medium_landscape/291/727731.jpg1
8.3%
Other values (2)2
16.7%

Most occurring characters

ValueCountFrequency (%)
/84
 
9.7%
a72
 
8.3%
t60
 
6.9%
s60
 
6.9%
m60
 
6.9%
p48
 
5.6%
e48
 
5.6%
.36
 
4.2%
c36
 
4.2%
d36
 
4.2%
Other values (22)324
37.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter612
70.8%
Other Punctuation132
 
15.3%
Decimal Number108
 
12.5%
Connector Punctuation12
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a72
11.8%
t60
9.8%
s60
9.8%
m60
9.8%
p48
 
7.8%
e48
 
7.8%
c36
 
5.9%
d36
 
5.9%
i36
 
5.9%
g24
 
3.9%
Other values (8)132
21.6%
Decimal Number
ValueCountFrequency (%)
228
25.9%
725
23.1%
917
15.7%
112
11.1%
310
 
9.3%
85
 
4.6%
44
 
3.7%
03
 
2.8%
53
 
2.8%
61
 
0.9%
Other Punctuation
ValueCountFrequency (%)
/84
63.6%
.36
27.3%
:12
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin612
70.8%
Common252
29.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
a72
11.8%
t60
9.8%
s60
9.8%
m60
9.8%
p48
 
7.8%
e48
 
7.8%
c36
 
5.9%
d36
 
5.9%
i36
 
5.9%
g24
 
3.9%
Other values (8)132
21.6%
Common
ValueCountFrequency (%)
/84
33.3%
.36
14.3%
228
 
11.1%
725
 
9.9%
917
 
6.7%
112
 
4.8%
_12
 
4.8%
:12
 
4.8%
310
 
4.0%
85
 
2.0%
Other values (4)11
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII864
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/84
 
9.7%
a72
 
8.3%
t60
 
6.9%
s60
 
6.9%
m60
 
6.9%
p48
 
5.6%
e48
 
5.6%
.36
 
4.2%
c36
 
4.2%
d36
 
4.2%
Other values (22)324
37.5%

image.original
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct12
Distinct (%)100.0%
Missing62
Missing (%)83.8%
Memory size720.0 B
https://static.tvmaze.com/uploads/images/original_untouched/294/737210.jpg
https://static.tvmaze.com/uploads/images/original_untouched/291/728291.jpg
https://static.tvmaze.com/uploads/images/original_untouched/293/733849.jpg
https://static.tvmaze.com/uploads/images/original_untouched/291/729339.jpg
https://static.tvmaze.com/uploads/images/original_untouched/292/730358.jpg
Other values (7)

Length

Max length74
Median length74
Mean length74
Min length74

Characters and Unicode

Total characters888
Distinct characters33
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)100.0%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/original_untouched/294/737210.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/original_untouched/291/728291.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/original_untouched/293/733849.jpg
4th rowhttps://static.tvmaze.com/uploads/images/original_untouched/291/729339.jpg
5th rowhttps://static.tvmaze.com/uploads/images/original_untouched/292/730358.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/294/737210.jpg1
 
1.4%
https://static.tvmaze.com/uploads/images/original_untouched/291/728291.jpg1
 
1.4%
https://static.tvmaze.com/uploads/images/original_untouched/293/733849.jpg1
 
1.4%
https://static.tvmaze.com/uploads/images/original_untouched/291/729339.jpg1
 
1.4%
https://static.tvmaze.com/uploads/images/original_untouched/292/730358.jpg1
 
1.4%
https://static.tvmaze.com/uploads/images/original_untouched/291/728205.jpg1
 
1.4%
https://static.tvmaze.com/uploads/images/original_untouched/289/724614.jpg1
 
1.4%
https://static.tvmaze.com/uploads/images/original_untouched/291/727577.jpg1
 
1.4%
https://static.tvmaze.com/uploads/images/original_untouched/291/727732.jpg1
 
1.4%
https://static.tvmaze.com/uploads/images/original_untouched/291/727731.jpg1
 
1.4%
Other values (2)2
 
2.7%
(Missing)62
83.8%

Length

2022-09-05T21:50:49.447629image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/294/737210.jpg1
8.3%
https://static.tvmaze.com/uploads/images/original_untouched/291/728291.jpg1
8.3%
https://static.tvmaze.com/uploads/images/original_untouched/293/733849.jpg1
8.3%
https://static.tvmaze.com/uploads/images/original_untouched/291/729339.jpg1
8.3%
https://static.tvmaze.com/uploads/images/original_untouched/292/730358.jpg1
8.3%
https://static.tvmaze.com/uploads/images/original_untouched/291/728205.jpg1
8.3%
https://static.tvmaze.com/uploads/images/original_untouched/289/724614.jpg1
8.3%
https://static.tvmaze.com/uploads/images/original_untouched/291/727577.jpg1
8.3%
https://static.tvmaze.com/uploads/images/original_untouched/291/727732.jpg1
8.3%
https://static.tvmaze.com/uploads/images/original_untouched/291/727731.jpg1
8.3%
Other values (2)2
16.7%

Most occurring characters

ValueCountFrequency (%)
/84
 
9.5%
t72
 
8.1%
a60
 
6.8%
s48
 
5.4%
o48
 
5.4%
i48
 
5.4%
m36
 
4.1%
u36
 
4.1%
e36
 
4.1%
c36
 
4.1%
Other values (23)384
43.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter636
71.6%
Other Punctuation132
 
14.9%
Decimal Number108
 
12.2%
Connector Punctuation12
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t72
 
11.3%
a60
 
9.4%
s48
 
7.5%
o48
 
7.5%
i48
 
7.5%
m36
 
5.7%
u36
 
5.7%
e36
 
5.7%
c36
 
5.7%
g36
 
5.7%
Other values (9)180
28.3%
Decimal Number
ValueCountFrequency (%)
228
25.9%
725
23.1%
917
15.7%
112
11.1%
310
 
9.3%
85
 
4.6%
44
 
3.7%
03
 
2.8%
53
 
2.8%
61
 
0.9%
Other Punctuation
ValueCountFrequency (%)
/84
63.6%
.36
27.3%
:12
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin636
71.6%
Common252
 
28.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
t72
 
11.3%
a60
 
9.4%
s48
 
7.5%
o48
 
7.5%
i48
 
7.5%
m36
 
5.7%
u36
 
5.7%
e36
 
5.7%
c36
 
5.7%
g36
 
5.7%
Other values (9)180
28.3%
Common
ValueCountFrequency (%)
/84
33.3%
.36
14.3%
228
 
11.1%
725
 
9.9%
917
 
6.7%
_12
 
4.8%
:12
 
4.8%
112
 
4.8%
310
 
4.0%
85
 
2.0%
Other values (4)11
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII888
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/84
 
9.5%
t72
 
8.1%
a60
 
6.8%
s48
 
5.4%
o48
 
5.4%
i48
 
5.4%
m36
 
4.1%
u36
 
4.1%
e36
 
4.1%
c36
 
4.1%
Other values (23)384
43.2%

_embedded.show.network.id
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct3
Distinct (%)100.0%
Missing71
Missing (%)95.9%
Memory size720.0 B
308.0
402.0
112.0

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters15
Distinct characters7
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)100.0%

Sample

1st row308.0
2nd row402.0
3rd row112.0

Common Values

ValueCountFrequency (%)
308.01
 
1.4%
402.01
 
1.4%
112.01
 
1.4%
(Missing)71
95.9%

Length

2022-09-05T21:50:49.537518image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:50:49.625328image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
308.01
33.3%
402.01
33.3%
112.01
33.3%

Most occurring characters

ValueCountFrequency (%)
05
33.3%
.3
20.0%
22
 
13.3%
12
 
13.3%
31
 
6.7%
81
 
6.7%
41
 
6.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number12
80.0%
Other Punctuation3
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
05
41.7%
22
 
16.7%
12
 
16.7%
31
 
8.3%
81
 
8.3%
41
 
8.3%
Other Punctuation
ValueCountFrequency (%)
.3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common15
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
05
33.3%
.3
20.0%
22
 
13.3%
12
 
13.3%
31
 
6.7%
81
 
6.7%
41
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII15
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
05
33.3%
.3
20.0%
22
 
13.3%
12
 
13.3%
31
 
6.7%
81
 
6.7%
41
 
6.7%

_embedded.show.network.name
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct3
Distinct (%)100.0%
Missing71
Missing (%)95.9%
Memory size720.0 B
ТНТ
Новий Канал
RTL4

Length

Max length11
Median length4
Mean length6
Min length3

Characters and Unicode

Total characters18
Distinct characters15
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)100.0%

Sample

1st rowТНТ
2nd rowНовий Канал
3rd rowRTL4

Common Values

ValueCountFrequency (%)
ТНТ1
 
1.4%
Новий Канал1
 
1.4%
RTL41
 
1.4%
(Missing)71
95.9%

Length

2022-09-05T21:50:49.722025image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:50:49.825421image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
тнт1
25.0%
новий1
25.0%
канал1
25.0%
rtl41
25.0%

Most occurring characters

ValueCountFrequency (%)
Т2
 
11.1%
Н2
 
11.1%
а2
 
11.1%
о1
 
5.6%
в1
 
5.6%
и1
 
5.6%
й1
 
5.6%
1
 
5.6%
К1
 
5.6%
н1
 
5.6%
Other values (5)5
27.8%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter8
44.4%
Lowercase Letter8
44.4%
Space Separator1
 
5.6%
Decimal Number1
 
5.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
а2
25.0%
о1
12.5%
в1
12.5%
и1
12.5%
й1
12.5%
н1
12.5%
л1
12.5%
Uppercase Letter
ValueCountFrequency (%)
Т2
25.0%
Н2
25.0%
К1
12.5%
R1
12.5%
T1
12.5%
L1
12.5%
Space Separator
ValueCountFrequency (%)
1
100.0%
Decimal Number
ValueCountFrequency (%)
41
100.0%

Most occurring scripts

ValueCountFrequency (%)
Cyrillic13
72.2%
Latin3
 
16.7%
Common2
 
11.1%

Most frequent character per script

Cyrillic
ValueCountFrequency (%)
Т2
15.4%
Н2
15.4%
а2
15.4%
о1
7.7%
в1
7.7%
и1
7.7%
й1
7.7%
К1
7.7%
н1
7.7%
л1
7.7%
Latin
ValueCountFrequency (%)
R1
33.3%
T1
33.3%
L1
33.3%
Common
ValueCountFrequency (%)
1
50.0%
41
50.0%

Most occurring blocks

ValueCountFrequency (%)
Cyrillic13
72.2%
ASCII5
 
27.8%

Most frequent character per block

Cyrillic
ValueCountFrequency (%)
Т2
15.4%
Н2
15.4%
а2
15.4%
о1
7.7%
в1
7.7%
и1
7.7%
й1
7.7%
К1
7.7%
н1
7.7%
л1
7.7%
ASCII
ValueCountFrequency (%)
1
20.0%
R1
20.0%
T1
20.0%
L1
20.0%
41
20.0%

_embedded.show.network.country.name
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct3
Distinct (%)100.0%
Missing71
Missing (%)95.9%
Memory size720.0 B
Russian Federation
Ukraine
Netherlands

Length

Max length18
Median length11
Mean length12
Min length7

Characters and Unicode

Total characters36
Distinct characters18
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)100.0%

Sample

1st rowRussian Federation
2nd rowUkraine
3rd rowNetherlands

Common Values

ValueCountFrequency (%)
Russian Federation1
 
1.4%
Ukraine1
 
1.4%
Netherlands1
 
1.4%
(Missing)71
95.9%

Length

2022-09-05T21:50:49.911161image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:50:50.004597image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
russian1
25.0%
federation1
25.0%
ukraine1
25.0%
netherlands1
25.0%

Most occurring characters

ValueCountFrequency (%)
e5
13.9%
a4
11.1%
n4
11.1%
s3
 
8.3%
i3
 
8.3%
r3
 
8.3%
d2
 
5.6%
t2
 
5.6%
U1
 
2.8%
h1
 
2.8%
Other values (8)8
22.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter31
86.1%
Uppercase Letter4
 
11.1%
Space Separator1
 
2.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e5
16.1%
a4
12.9%
n4
12.9%
s3
9.7%
i3
9.7%
r3
9.7%
d2
 
6.5%
t2
 
6.5%
h1
 
3.2%
k1
 
3.2%
Other values (3)3
9.7%
Uppercase Letter
ValueCountFrequency (%)
U1
25.0%
N1
25.0%
R1
25.0%
F1
25.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin35
97.2%
Common1
 
2.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e5
14.3%
a4
11.4%
n4
11.4%
s3
8.6%
i3
8.6%
r3
8.6%
d2
 
5.7%
t2
 
5.7%
U1
 
2.9%
h1
 
2.9%
Other values (7)7
20.0%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII36
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e5
13.9%
a4
11.1%
n4
11.1%
s3
 
8.3%
i3
 
8.3%
r3
 
8.3%
d2
 
5.6%
t2
 
5.6%
U1
 
2.8%
h1
 
2.8%
Other values (8)8
22.2%

_embedded.show.network.country.code
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct3
Distinct (%)100.0%
Missing71
Missing (%)95.9%
Memory size720.0 B
RU
UA
NL

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters6
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)100.0%

Sample

1st rowRU
2nd rowUA
3rd rowNL

Common Values

ValueCountFrequency (%)
RU1
 
1.4%
UA1
 
1.4%
NL1
 
1.4%
(Missing)71
95.9%

Length

2022-09-05T21:50:50.084543image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:50:50.170484image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
ru1
33.3%
ua1
33.3%
nl1
33.3%

Most occurring characters

ValueCountFrequency (%)
U2
33.3%
R1
16.7%
A1
16.7%
N1
16.7%
L1
16.7%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter6
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
U2
33.3%
R1
16.7%
A1
16.7%
N1
16.7%
L1
16.7%

Most occurring scripts

ValueCountFrequency (%)
Latin6
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
U2
33.3%
R1
16.7%
A1
16.7%
N1
16.7%
L1
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII6
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
U2
33.3%
R1
16.7%
A1
16.7%
N1
16.7%
L1
16.7%

_embedded.show.network.country.timezone
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct3
Distinct (%)100.0%
Missing71
Missing (%)95.9%
Memory size720.0 B
Asia/Kamchatka
Europe/Zaporozhye
Europe/Amsterdam

Length

Max length17
Median length16
Mean length15.66666667
Min length14

Characters and Unicode

Total characters47
Distinct characters21
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)100.0%

Sample

1st rowAsia/Kamchatka
2nd rowEurope/Zaporozhye
3rd rowEurope/Amsterdam

Common Values

ValueCountFrequency (%)
Asia/Kamchatka1
 
1.4%
Europe/Zaporozhye1
 
1.4%
Europe/Amsterdam1
 
1.4%
(Missing)71
95.9%

Length

2022-09-05T21:50:50.255064image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:50:50.352422image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
asia/kamchatka1
33.3%
europe/zaporozhye1
33.3%
europe/amsterdam1
33.3%

Most occurring characters

ValueCountFrequency (%)
a6
12.8%
e4
 
8.5%
r4
 
8.5%
o4
 
8.5%
/3
 
6.4%
m3
 
6.4%
p3
 
6.4%
A2
 
4.3%
h2
 
4.3%
t2
 
4.3%
Other values (11)14
29.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter38
80.9%
Uppercase Letter6
 
12.8%
Other Punctuation3
 
6.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a6
15.8%
e4
10.5%
r4
10.5%
o4
10.5%
m3
7.9%
p3
7.9%
h2
 
5.3%
t2
 
5.3%
s2
 
5.3%
u2
 
5.3%
Other values (6)6
15.8%
Uppercase Letter
ValueCountFrequency (%)
A2
33.3%
E2
33.3%
Z1
16.7%
K1
16.7%
Other Punctuation
ValueCountFrequency (%)
/3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin44
93.6%
Common3
 
6.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
a6
13.6%
e4
 
9.1%
r4
 
9.1%
o4
 
9.1%
m3
 
6.8%
p3
 
6.8%
A2
 
4.5%
h2
 
4.5%
t2
 
4.5%
s2
 
4.5%
Other values (10)12
27.3%
Common
ValueCountFrequency (%)
/3
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII47
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a6
12.8%
e4
 
8.5%
r4
 
8.5%
o4
 
8.5%
/3
 
6.4%
m3
 
6.4%
p3
 
6.4%
A2
 
4.3%
h2
 
4.3%
t2
 
4.3%
Other values (11)14
29.8%

_embedded.show.network.officialSite
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing74
Missing (%)100.0%
Memory size720.0 B

_embedded.show._links.nextepisode.href
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct5
Distinct (%)100.0%
Missing69
Missing (%)93.2%
Memory size720.0 B
https://api.tvmaze.com/episodes/2309443
https://api.tvmaze.com/episodes/2375640
https://api.tvmaze.com/episodes/2383184
https://api.tvmaze.com/episodes/2383145
https://api.tvmaze.com/episodes/2379703

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters195
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)100.0%

Sample

1st rowhttps://api.tvmaze.com/episodes/2309443
2nd rowhttps://api.tvmaze.com/episodes/2375640
3rd rowhttps://api.tvmaze.com/episodes/2383184
4th rowhttps://api.tvmaze.com/episodes/2383145
5th rowhttps://api.tvmaze.com/episodes/2379703

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/episodes/23094431
 
1.4%
https://api.tvmaze.com/episodes/23756401
 
1.4%
https://api.tvmaze.com/episodes/23831841
 
1.4%
https://api.tvmaze.com/episodes/23831451
 
1.4%
https://api.tvmaze.com/episodes/23797031
 
1.4%
(Missing)69
93.2%

Length

2022-09-05T21:50:50.435741image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:50:50.529380image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/23094431
20.0%
https://api.tvmaze.com/episodes/23756401
20.0%
https://api.tvmaze.com/episodes/23831841
20.0%
https://api.tvmaze.com/episodes/23831451
20.0%
https://api.tvmaze.com/episodes/23797031
20.0%

Most occurring characters

ValueCountFrequency (%)
/20
 
10.3%
p15
 
7.7%
s15
 
7.7%
e15
 
7.7%
t15
 
7.7%
a10
 
5.1%
i10
 
5.1%
.10
 
5.1%
m10
 
5.1%
o10
 
5.1%
Other values (16)65
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter125
64.1%
Other Punctuation35
 
17.9%
Decimal Number35
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
p15
12.0%
s15
12.0%
e15
12.0%
t15
12.0%
a10
8.0%
i10
8.0%
m10
8.0%
o10
8.0%
h5
 
4.0%
d5
 
4.0%
Other values (3)15
12.0%
Decimal Number
ValueCountFrequency (%)
39
25.7%
45
14.3%
25
14.3%
03
 
8.6%
73
 
8.6%
83
 
8.6%
92
 
5.7%
52
 
5.7%
12
 
5.7%
61
 
2.9%
Other Punctuation
ValueCountFrequency (%)
/20
57.1%
.10
28.6%
:5
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin125
64.1%
Common70
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
/20
28.6%
.10
14.3%
39
12.9%
45
 
7.1%
25
 
7.1%
:5
 
7.1%
03
 
4.3%
73
 
4.3%
83
 
4.3%
92
 
2.9%
Other values (3)5
 
7.1%
Latin
ValueCountFrequency (%)
p15
12.0%
s15
12.0%
e15
12.0%
t15
12.0%
a10
8.0%
i10
8.0%
m10
8.0%
o10
8.0%
h5
 
4.0%
d5
 
4.0%
Other values (3)15
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII195
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/20
 
10.3%
p15
 
7.7%
s15
 
7.7%
e15
 
7.7%
t15
 
7.7%
a10
 
5.1%
i10
 
5.1%
.10
 
5.1%
m10
 
5.1%
o10
 
5.1%
Other values (16)65
33.3%

_embedded.show.image
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing74
Missing (%)100.0%
Memory size720.0 B

_embedded.show.dvdCountry.name
Categorical

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing73
Missing (%)98.6%
Memory size720.0 B
Ukraine

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters7
Distinct characters7
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowUkraine

Common Values

ValueCountFrequency (%)
Ukraine1
 
1.4%
(Missing)73
98.6%

Length

2022-09-05T21:50:50.614726image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:50:50.696021image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
ukraine1
100.0%

Most occurring characters

ValueCountFrequency (%)
U1
14.3%
k1
14.3%
r1
14.3%
a1
14.3%
i1
14.3%
n1
14.3%
e1
14.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter6
85.7%
Uppercase Letter1
 
14.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
k1
16.7%
r1
16.7%
a1
16.7%
i1
16.7%
n1
16.7%
e1
16.7%
Uppercase Letter
ValueCountFrequency (%)
U1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin7
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
U1
14.3%
k1
14.3%
r1
14.3%
a1
14.3%
i1
14.3%
n1
14.3%
e1
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII7
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
U1
14.3%
k1
14.3%
r1
14.3%
a1
14.3%
i1
14.3%
n1
14.3%
e1
14.3%

_embedded.show.dvdCountry.code
Categorical

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing73
Missing (%)98.6%
Memory size720.0 B
UA

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowUA

Common Values

ValueCountFrequency (%)
UA1
 
1.4%
(Missing)73
98.6%

Length

2022-09-05T21:50:50.779257image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:50:50.871583image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
ua1
100.0%

Most occurring characters

ValueCountFrequency (%)
U1
50.0%
A1
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter2
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
U1
50.0%
A1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
U1
50.0%
A1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII2
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
U1
50.0%
A1
50.0%

_embedded.show.dvdCountry.timezone
Categorical

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing73
Missing (%)98.6%
Memory size720.0 B
Europe/Zaporozhye

Length

Max length17
Median length17
Mean length17
Min length17

Characters and Unicode

Total characters17
Distinct characters12
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowEurope/Zaporozhye

Common Values

ValueCountFrequency (%)
Europe/Zaporozhye1
 
1.4%
(Missing)73
98.6%

Length

2022-09-05T21:50:50.957537image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:50:51.035298image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
europe/zaporozhye1
100.0%

Most occurring characters

ValueCountFrequency (%)
o3
17.6%
r2
11.8%
p2
11.8%
e2
11.8%
E1
 
5.9%
u1
 
5.9%
/1
 
5.9%
Z1
 
5.9%
a1
 
5.9%
z1
 
5.9%
Other values (2)2
11.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter14
82.4%
Uppercase Letter2
 
11.8%
Other Punctuation1
 
5.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o3
21.4%
r2
14.3%
p2
14.3%
e2
14.3%
u1
 
7.1%
a1
 
7.1%
z1
 
7.1%
h1
 
7.1%
y1
 
7.1%
Uppercase Letter
ValueCountFrequency (%)
E1
50.0%
Z1
50.0%
Other Punctuation
ValueCountFrequency (%)
/1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin16
94.1%
Common1
 
5.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
o3
18.8%
r2
12.5%
p2
12.5%
e2
12.5%
E1
 
6.2%
u1
 
6.2%
Z1
 
6.2%
a1
 
6.2%
z1
 
6.2%
h1
 
6.2%
Common
ValueCountFrequency (%)
/1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII17
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o3
17.6%
r2
11.8%
p2
11.8%
e2
11.8%
E1
 
5.9%
u1
 
5.9%
/1
 
5.9%
Z1
 
5.9%
a1
 
5.9%
z1
 
5.9%
Other values (2)2
11.8%

_embedded.show.webChannel
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing74
Missing (%)100.0%
Memory size720.0 B

Interactions

2022-09-05T21:50:40.277909image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:32.498142image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:33.363719image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:34.199760image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:34.949436image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:35.703100image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:36.532364image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:37.284974image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:38.028158image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:38.747490image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:39.474042image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:40.353618image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:32.671835image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:33.439769image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:34.263249image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:35.013189image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:35.777866image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:36.599760image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:37.350605image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:38.088033image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:38.810508image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:39.546274image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:40.430445image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:32.740199image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:33.522348image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:34.333781image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:35.082997image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:35.862859image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:36.670632image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:37.421274image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:38.156224image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:38.879886image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:39.627391image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:40.505674image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:32.814551image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:33.602770image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:34.404507image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:35.148663image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:35.946892image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:36.737884image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:37.491547image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:38.223080image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:38.947503image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:39.706615image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:40.583929image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:32.892005image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:33.682099image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:34.470678image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:35.214353image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:36.028871image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:36.805495image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:37.559242image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:38.289158image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:39.015357image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:39.776792image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:40.664175image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:32.966125image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:33.764212image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:34.538530image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:35.288303image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:36.105205image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:36.874000image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:37.628656image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:38.356580image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:39.076857image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:39.844997image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:40.745155image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:33.035990image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:33.844649image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:34.604473image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:35.353656image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:36.179860image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:36.939904image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:37.696135image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:38.428972image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:39.143423image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:39.912712image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:40.825500image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:33.101531image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:33.926174image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:34.673716image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:35.421792image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:36.257149image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:37.006782image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:37.765339image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:38.492873image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:39.209832image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:39.981697image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:40.894637image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:33.164030image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:33.994477image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:34.739775image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:35.483666image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:36.324977image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:37.077711image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:37.827789image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:38.553982image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:39.271687image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:40.048716image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:40.966487image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:33.226373image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:34.061256image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:34.806520image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:35.549525image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:36.393008image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:37.148171image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:37.892987image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:38.617595image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:39.336022image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:40.119034image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:41.041997image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:33.293980image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:34.130966image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:34.876985image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:35.624866image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:36.463763image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:37.216967image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:37.961292image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:38.681695image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:39.406116image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:50:40.199400image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Correlations

2022-09-05T21:50:51.131727image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2022-09-05T21:50:51.398137image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2022-09-05T21:50:51.632056image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2022-09-05T21:50:51.922626image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2022-09-05T21:50:41.445919image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2022-09-05T21:50:42.168116image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.
2022-09-05T21:50:42.645910image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

Sample

First rows

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02007756https://www.tvmaze.com/episodes/2007756/stand-up-autsajd-1x11-pavel-dedisev-17-minut-serebraПавел Дедищев "17 минут серебра"111regular2020-12-2912:002020-12-29T00:00:00+00:0020.0NaNNoneNaNhttps://api.tvmaze.com/episodes/200775651065https://www.tvmaze.com/shows/51065/stand-up-autsajdStand Up АутсайдVarietyRussian[]Ended40.028.02020-10-132020-12-31https://premier.one/show/13734[Monday]NaN4NaN21.0YouTubeNaNhttps://www.youtube.comNaNNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/277/693293.jpghttps://static.tvmaze.com/uploads/images/original_untouched/277/693293.jpg<p>Solo performances of stand-up comedians from the underground and popular TV and Internet projects. Each new release is a new concert with its own atmosphere and humor.</p>1616719192https://api.tvmaze.com/shows/51065https://api.tvmaze.com/episodes/2007760NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
11987860https://www.tvmaze.com/episodes/1987860/blic-krik-1x12-12-nurlan-saburov-t-fest-garik-oganisan-rustam-reptiloid-emir-kasokov#12: НУРЛАН САБУРОВ, T-Fest, ГАРИК ОГАНИСЯН, РУСТАМ РЕПТИЛОИД, ЭМИР КАШОКОВ112regular2020-12-2912:002020-12-29T00:00:00+00:0030.0NaNNoneNaNhttps://api.tvmaze.com/episodes/198786052044https://www.tvmaze.com/shows/52044/blic-krikБлиц-крикGame ShowRussian[Comedy]Running43.033.02019-08-20Nonehttps://the-hole.tv/shows/blitz-krik[]NaN21NaN529.0The HoleNaNhttps://the-hole.tv/NaNNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/419/1048239.jpghttps://static.tvmaze.com/uploads/images/original_untouched/419/1048239.jpg<p>Юмористическое шоу, где знания участников так же важны, как и юмор! Игра состоит из трех раундов. Ведущий зачитывает начало цитаты, стихотворения или факта, а конкурсант должен закончить их либо смешно, либо правильно! Победит тот, кто окажется самым умным и веселым!</p>1661014123https://api.tvmaze.com/shows/52044https://api.tvmaze.com/episodes/2376787Russian FederationRUAsia/KamchatkaNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
22008031https://www.tvmaze.com/episodes/2008031/lab-s-antonom-belaevym-2x10-therr-maitzTherr Maitz210regular2020-12-292020-12-29T00:00:00+00:0034.0NaNNoneNaNhttps://api.tvmaze.com/episodes/200803152933https://www.tvmaze.com/shows/52933/lab-s-antonom-belaevymLAB с Антоном БеляевымDocumentaryRussian[Music]To Be Determined26.025.02019-12-17Nonehttps://premier.one/show/lab-laboratoriya-muzyki-antona-belyaeva23:45[Saturday]NaN25NaN381.0КиноПоиск HDNaNhttps://hd.kinopoisk.ru/NaNNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/379/948045.jpghttps://static.tvmaze.com/uploads/images/original_untouched/379/948045.jpg<p>Russian music artists reveal themselves from unexpected sides in the Anton Belyaev's show.</p>1654035738https://api.tvmaze.com/shows/52933https://api.tvmaze.com/episodes/2245512Russian FederationRUAsia/Kamchatkahttps://static.tvmaze.com/uploads/images/medium_landscape/294/737210.jpghttps://static.tvmaze.com/uploads/images/original_untouched/294/737210.jpg308.0ТНТRussian FederationRUAsia/KamchatkaNaNNaNNaNNaNNaNNaNNaN
31964569https://www.tvmaze.com/episodes/1964569/core-sense-1x13-episode-13Episode 13113regular2020-12-2910:002020-12-29T02:00:00+00:0024.0NaNNoneNaNhttps://api.tvmaze.com/episodes/196456951336https://www.tvmaze.com/shows/51336/core-senseCore SenseAnimationChinese[Action, Anime, Science-Fiction]Running24.024.02020-10-13Nonehttps://www.bilibili.com/bangumi/media/md2822306410:00[Tuesday]NaN29NaN51.0BilibiliNaNNoneNaNNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/278/696645.jpghttps://static.tvmaze.com/uploads/images/original_untouched/278/696645.jpg<p>The power of beginnings, the energy of the core stone; one may find it good, one may find it evil. During a normal investigation, Yue Juntian finds himself drawn into the battle between the 'beginnings' of Yun City; Jiang Xin arrives in Yun City to stop Li Zunyuan's plan to take over. The two influence each other - one solves the mystery of their birth, the other redeems themselves. Together, they oppose Li Zunyuan.<br /> </p>1604587119https://api.tvmaze.com/shows/51336https://api.tvmaze.com/episodes/1964569ChinaCNAsia/ShanghaiNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
42052513https://www.tvmaze.com/episodes/2052513/wu-shen-zhu-zai-1x88-episode-88Episode 88188regular2020-12-2910:002020-12-29T02:00:00+00:008.0NaNNoneNaNhttps://api.tvmaze.com/episodes/205251354033https://www.tvmaze.com/shows/54033/wu-shen-zhu-zaiWu Shen Zhu ZaiAnimationChinese[Action, Adventure, Anime, Fantasy]Running8.08.02020-03-08Nonehttps://v.qq.com/detail/m/7q544xyrava3vxf.html10:00[Tuesday, Sunday]NaN82NaN104.0Tencent QQNaNhttps://v.qq.com/NaNNaN379070.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/299/748854.jpghttps://static.tvmaze.com/uploads/images/original_untouched/299/748854.jpg<p>The protagonist Qin Chen, who was originally the top genius in the military domain, was conspired by the people to fall into the death canyon in the forbidden land of the mainland. Qin Chen, who was inevitably dead, unexpectedly triggered the power of the mysterious ancient sword.<br /><br />Three hundred years later, in a remote part of the Tianwu mainland, a boy of the same name accidentally inherited Qin Chen's will. As the beloved grandson of King Dingwu of the Daqi National Army, due to the birth father's birth, the mother and son were treated coldly in Dingwu's palace and lived together. In order to rewrite the myth of the strong man in hope of the sun, and to protect everything he loves, Qin Chen resolutely took up the responsibility of maintaining the five kingdoms of the world and set foot on the road of martial arts again.</p>1649423444https://api.tvmaze.com/shows/54033https://api.tvmaze.com/episodes/2309442ChinaCNAsia/ShanghaiNaNNaNNaNNaNNaNNaNNaNNaNhttps://api.tvmaze.com/episodes/2309443NaNNaNNaNNaNNaN
51993658https://www.tvmaze.com/episodes/1993658/7-days-of-romance-2x03-episode-3Episode 323regular2020-12-292020-12-29T03:00:00+00:0015.0NaNNoneNaNhttps://api.tvmaze.com/episodes/199365844276https://www.tvmaze.com/shows/44276/7-days-of-romance7 Days of RomanceScriptedKorean[Drama, Romance]EndedNaN15.02019-10-082021-01-20None[Tuesday, Wednesday]NaN81NaN380.0SeeznNaNhttps://www.seezntv.com/NaNNaN370873.0tt13423446https://static.tvmaze.com/uploads/images/medium_portrait/290/727378.jpghttps://static.tvmaze.com/uploads/images/original_untouched/290/727378.jpg<p>Da Eun works part-time and Kim Byul is an idol in her 5th years since debut. These two girls who look alike decide to change each other's lives just for 7 days. It tells the romantic encounters of these 2 girls.</p>1650033745https://api.tvmaze.com/shows/44276https://api.tvmaze.com/episodes/1993665Korea, Republic ofKRAsia/SeoulNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
62096302https://www.tvmaze.com/episodes/2096302/no-turning-back-romance-1x07-7717regular2020-12-292020-12-29T03:00:00+00:0012.0NaNNoneNaNhttps://api.tvmaze.com/episodes/209630255002https://www.tvmaze.com/shows/55002/no-turning-back-romanceNo Turning Back RomanceScriptedKorean[]EndedNaN12.02020-12-082021-01-06None[Tuesday, Wednesday]NaN23NaN30.0Naver TVCastNaNhttps://tv.naver.com/NaNNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/319/799196.jpghttps://static.tvmaze.com/uploads/images/original_untouched/319/799196.jpg<p>A teen romance of So Dam, a sixteen-year-old girl, who has never dated before but she receives her first-ever love confession from a mysterious boy. She is looking for the boy who secretly confessed to her while she was asleep on her desk. The clues include a male voice, mango fruit scent and gym uniform. She must piece the puzzle to find that person among the likely candidates that include hot shots Park Ji Hoo, Jeong Han Kyul, and Joo In Hyuk.</p>1621617231https://api.tvmaze.com/shows/55002https://api.tvmaze.com/episodes/2096309Korea, Republic ofKRAsia/SeoulNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
72324423https://www.tvmaze.com/episodes/2324423/unique-lady-2x11-episode-11Episode 11211regular2020-12-2912:002020-12-29T04:00:00+00:0040.0NaNNoneNaNhttps://api.tvmaze.com/episodes/232442341490https://www.tvmaze.com/shows/41490/unique-ladyUnique LadyScriptedChinese[Drama, Comedy, Romance]Ended38.042.02019-01-172021-01-07http://www.iqiyi.com/a_19rrhvpyyp.html[Thursday, Friday, Saturday]NaN35NaN67.0iQIYINaNhttps://www.iq.com/NaNNaN360222.0tt11939550https://static.tvmaze.com/uploads/images/medium_portrait/189/473411.jpghttps://static.tvmaze.com/uploads/images/original_untouched/189/473411.jpg<p>Lin Luo Jing accidentally gets drawn into a game world where she is the daughter of the prime minister and meets all kind of beautiful men with different personalities. Among them are a sword deity, an imperial bodyguard, a playful rich man and an arrogant prince. The system informs her that she can only return to the real world after she finds her true love. While there seems tobe an abundance of good men around Luo Jing, there is one man she can't stand at all: the prince of the barbarian Yuan Kingdom Zhong Wu Mei. But out of all men, she ends up in an arranged marriage with Wu Mei.</p><p>Thus begins their love-hate relationship and her journey to find true love in order to win the game.</p>1654382071https://api.tvmaze.com/shows/41490https://api.tvmaze.com/episodes/2324440NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
82324424https://www.tvmaze.com/episodes/2324424/unique-lady-2x12-episode-12Episode 12212regular2020-12-2912:002020-12-29T04:00:00+00:0038.0NaNNoneNaNhttps://api.tvmaze.com/episodes/232442441490https://www.tvmaze.com/shows/41490/unique-ladyUnique LadyScriptedChinese[Drama, Comedy, Romance]Ended38.042.02019-01-172021-01-07http://www.iqiyi.com/a_19rrhvpyyp.html[Thursday, Friday, Saturday]NaN35NaN67.0iQIYINaNhttps://www.iq.com/NaNNaN360222.0tt11939550https://static.tvmaze.com/uploads/images/medium_portrait/189/473411.jpghttps://static.tvmaze.com/uploads/images/original_untouched/189/473411.jpg<p>Lin Luo Jing accidentally gets drawn into a game world where she is the daughter of the prime minister and meets all kind of beautiful men with different personalities. Among them are a sword deity, an imperial bodyguard, a playful rich man and an arrogant prince. The system informs her that she can only return to the real world after she finds her true love. While there seems tobe an abundance of good men around Luo Jing, there is one man she can't stand at all: the prince of the barbarian Yuan Kingdom Zhong Wu Mei. But out of all men, she ends up in an arranged marriage with Wu Mei.</p><p>Thus begins their love-hate relationship and her journey to find true love in order to win the game.</p>1654382071https://api.tvmaze.com/shows/41490https://api.tvmaze.com/episodes/2324440NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
92068352https://www.tvmaze.com/episodes/2068352/doomsday-awakening-2x03-episode-3Episode 323regular2020-12-292020-12-29T04:00:00+00:0015.0NaNNoneNaNhttps://api.tvmaze.com/episodes/206835248673https://www.tvmaze.com/shows/48673/doomsday-awakeningDoomsday AwakeningAnimationChinese[Action, Anime, Science-Fiction, War]Running15.015.02018-05-24Nonehttps://v.qq.com/detail/j/jaqpncskrgv28oo.html[Tuesday]NaN75NaN104.0Tencent QQNaNhttps://v.qq.com/NaNNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/261/653909.jpghttps://static.tvmaze.com/uploads/images/original_untouched/261/653909.jpgNone1618076715https://api.tvmaze.com/shows/48673https://api.tvmaze.com/episodes/2068363ChinaCNAsia/ShanghaiNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN

Last rows

idurlnameseasonnumbertypeairdateairtimeairstampruntimeimagesummaryrating.average_links.self.href_embedded.show.id_embedded.show.url_embedded.show.name_embedded.show.type_embedded.show.language_embedded.show.genres_embedded.show.status_embedded.show.runtime_embedded.show.averageRuntime_embedded.show.premiered_embedded.show.ended_embedded.show.officialSite_embedded.show.schedule.time_embedded.show.schedule.days_embedded.show.rating.average_embedded.show.weight_embedded.show.network_embedded.show.webChannel.id_embedded.show.webChannel.name_embedded.show.webChannel.country_embedded.show.webChannel.officialSite_embedded.show.dvdCountry_embedded.show.externals.tvrage_embedded.show.externals.thetvdb_embedded.show.externals.imdb_embedded.show.image.medium_embedded.show.image.original_embedded.show.summary_embedded.show.updated_embedded.show._links.self.href_embedded.show._links.previousepisode.href_embedded.show.webChannel.country.name_embedded.show.webChannel.country.code_embedded.show.webChannel.country.timezoneimage.mediumimage.original_embedded.show.network.id_embedded.show.network.name_embedded.show.network.country.name_embedded.show.network.country.code_embedded.show.network.country.timezone_embedded.show.network.officialSite_embedded.show._links.nextepisode.href_embedded.show.image_embedded.show.dvdCountry.name_embedded.show.dvdCountry.code_embedded.show.dvdCountry.timezone_embedded.show.webChannel
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652165009https://www.tvmaze.com/episodes/2165009/all-about-android-2020-12-29-2020-in-the-rear-view2020 in the Rear View202052regular2020-12-292020-12-29T17:00:00+00:0090.0NaNNoneNaNhttps://api.tvmaze.com/episodes/216500917633https://www.tvmaze.com/shows/17633/all-about-androidAll About AndroidNewsEnglish[]RunningNaN90.02011-03-29Nonehttps://twit.tv/shows/all-about-android[Tuesday]NaN44NaN102.0TwitNaNNoneNaNNaN260436.0tt3589312https://static.tvmaze.com/uploads/images/medium_portrait/59/148354.jpghttps://static.tvmaze.com/uploads/images/original_untouched/59/148354.jpg<p><b>All About Android </b>delivers everything you want to know about Android each week -- the biggest news, freshest hardware, best apps and geekiest how-to's -- with Android enthusiasts Jason Howell, Florence Ion, Ron Richards, and a variety of special guests along the way.</p>1653765273https://api.tvmaze.com/shows/17633https://api.tvmaze.com/episodes/2335726United StatesUSAmerica/New_YorkNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
661968004https://www.tvmaze.com/episodes/1968004/a-teacher-1x10-episode-10Episode 10110regular2020-12-292020-12-29T17:00:00+00:0030.0NaN<p>Claire and Eric have seemingly moved on with their lives, but a chance encounter brings new truths to light.<br /> </p>7.3https://api.tvmaze.com/episodes/196800438339https://www.tvmaze.com/shows/38339/a-teacherA TeacherScriptedEnglish[Drama]EndedNaN27.02020-11-102020-12-29https://www.hulu.com/series/a-teacher-1c871218-05b1-4c66-a22f-260b2cb9bbf9[Tuesday]5.894NaN2.0HuluNaNhttps://www.hulu.com/NaNNaN352440.0tt10680614https://static.tvmaze.com/uploads/images/medium_portrait/272/681431.jpghttps://static.tvmaze.com/uploads/images/original_untouched/272/681431.jpg<p><b>A Teacher</b> examines the complexities and consequences of an illegal relationship between a female teacher, Claire and her male high school student, Eric. Dissatisfied in their own lives, Claire and Eric discover an undeniable escape in each other, but their relationship accelerates faster than anticipated and the permanent damage becomes impossible to ignore.</p>1637344861https://api.tvmaze.com/shows/38339https://api.tvmaze.com/episodes/1968004United StatesUSAmerica/New_Yorkhttps://static.tvmaze.com/uploads/images/medium_landscape/289/724614.jpghttps://static.tvmaze.com/uploads/images/original_untouched/289/724614.jpgNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
672192627https://www.tvmaze.com/episodes/2192627/diti-proti-zirok-2x13-vypusk-13-artem-fedeckij-masa-efrosinina-amador-lopesВыпуск 13 (Артем Федецкий, Маша Ефросинина, Амадор Лопес)213regular2020-12-2919:002020-12-29T17:00:00+00:0090.0NaNNoneNaNhttps://api.tvmaze.com/episodes/219262744675https://www.tvmaze.com/shows/44675/diti-proti-zirokДіти проти зірокGame ShowUkrainian[Action, Family]Running90.090.02019-09-25Nonehttps://novy.tv/ua/deti-protiv-zvezd/19:00[Wednesday]NaN22NaN21.0YouTubeNaNhttps://www.youtube.comNaNNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/365/913800.jpghttps://static.tvmaze.com/uploads/images/original_untouched/365/913800.jpgNone1640952799https://api.tvmaze.com/shows/44675https://api.tvmaze.com/episodes/2245693NaNNaNNaNNaNNaN402.0Новий КаналUkraineUAEurope/ZaporozhyeNaNNaNNaNUkraineUAEurope/ZaporozhyeNaN
681979306https://www.tvmaze.com/episodes/1979306/familiekokkene-1x06-vegetarfestVegetarfest16regular2020-12-2918:002020-12-29T17:00:00+00:0060.0NaNNoneNaNhttps://api.tvmaze.com/episodes/197930649903https://www.tvmaze.com/shows/49903/familiekokkeneFamiliekokkeneRealityNorwegian[Food]Running60.060.02020-11-27Nonehttps://tv.nrk.no/serie/familiekokkene18:00[Saturday]NaN4NaN238.0NRK TVNaNNoneNaNNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/285/713504.jpghttps://static.tvmaze.com/uploads/images/original_untouched/285/713504.jpg<p>Six families with different backgrounds and a big interest in food compete to become Norways best home chef.</p>1607887175https://api.tvmaze.com/shows/49903https://api.tvmaze.com/episodes/1982924NorwayNOEurope/OsloNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
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701994076https://www.tvmaze.com/episodes/1994076/celebrity-a-21st-century-story-1x01-episode-one-ordinary-peopleEpisode One Ordinary People11regular2020-12-2921:002020-12-29T21:00:00+00:0060.0NaN<p>The first episode examines how the Beckhams changed the model of the celebrity power couple, while the rise of reality TV led to a gigantic influx of people gaining overnight fame, fed by a press that saw an easy source of material. The programme also examines how leaked sex tapes changed the nature of celebrity scandal.</p>NaNhttps://api.tvmaze.com/episodes/199407652661https://www.tvmaze.com/shows/52661/celebrity-a-21st-century-storyCelebrity: A 21st-Century StoryDocumentaryEnglish[History]To Be Determined60.060.02020-12-29Nonehttps://www.bbc.co.uk/programmes/m000qsk121:00[Tuesday]NaN27NaN26.0BBC iPlayerNaNhttps://www.bbc.co.uk/iplayerNaNNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/291/727584.jpghttps://static.tvmaze.com/uploads/images/original_untouched/291/727584.jpg<p>The world of celebrity has been transformed since the turn of the century, driven by some of the most dramatic technological and cultural developments in recent times.</p><p>This series charting the explosion in celebrity culture.</p>1611355220https://api.tvmaze.com/shows/52661https://api.tvmaze.com/episodes/1994079United KingdomGBEurope/Londonhttps://static.tvmaze.com/uploads/images/medium_landscape/291/727732.jpghttps://static.tvmaze.com/uploads/images/original_untouched/291/727732.jpgNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
711994077https://www.tvmaze.com/episodes/1994077/celebrity-a-21st-century-story-1x02-episode-two-trainwreckEpisode Two Trainwreck12regular2020-12-2921:002020-12-29T21:00:00+00:0060.0NaN<p>Charting the story of celebrity in the late noughties, this film looks at how different groups cashed in on the public's insatiable appetite for access to the famous.</p>NaNhttps://api.tvmaze.com/episodes/199407752661https://www.tvmaze.com/shows/52661/celebrity-a-21st-century-storyCelebrity: A 21st-Century StoryDocumentaryEnglish[History]To Be Determined60.060.02020-12-29Nonehttps://www.bbc.co.uk/programmes/m000qsk121:00[Tuesday]NaN27NaN26.0BBC iPlayerNaNhttps://www.bbc.co.uk/iplayerNaNNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/291/727584.jpghttps://static.tvmaze.com/uploads/images/original_untouched/291/727584.jpg<p>The world of celebrity has been transformed since the turn of the century, driven by some of the most dramatic technological and cultural developments in recent times.</p><p>This series charting the explosion in celebrity culture.</p>1611355220https://api.tvmaze.com/shows/52661https://api.tvmaze.com/episodes/1994079United KingdomGBEurope/Londonhttps://static.tvmaze.com/uploads/images/medium_landscape/291/727731.jpghttps://static.tvmaze.com/uploads/images/original_untouched/291/727731.jpgNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
721994078https://www.tvmaze.com/episodes/1994078/celebrity-a-21st-century-story-1x03-episode-three-lust-for-likesEpisode Three Lust for Likes13regular2020-12-2921:002020-12-29T21:00:00+00:0060.0NaN<p>This film tells the story of how celebrities capitalised on a digital revolution in order to sidestep the traditional routes to fame.</p>NaNhttps://api.tvmaze.com/episodes/199407852661https://www.tvmaze.com/shows/52661/celebrity-a-21st-century-storyCelebrity: A 21st-Century StoryDocumentaryEnglish[History]To Be Determined60.060.02020-12-29Nonehttps://www.bbc.co.uk/programmes/m000qsk121:00[Tuesday]NaN27NaN26.0BBC iPlayerNaNhttps://www.bbc.co.uk/iplayerNaNNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/291/727584.jpghttps://static.tvmaze.com/uploads/images/original_untouched/291/727584.jpg<p>The world of celebrity has been transformed since the turn of the century, driven by some of the most dramatic technological and cultural developments in recent times.</p><p>This series charting the explosion in celebrity culture.</p>1611355220https://api.tvmaze.com/shows/52661https://api.tvmaze.com/episodes/1994079United KingdomGBEurope/Londonhttps://static.tvmaze.com/uploads/images/medium_landscape/291/727729.jpghttps://static.tvmaze.com/uploads/images/original_untouched/291/727729.jpgNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
731994079https://www.tvmaze.com/episodes/1994079/celebrity-a-21st-century-story-1x04-episode-four-power-grabEpisode Four Power Grab14regular2020-12-2921:002020-12-29T21:00:00+00:0060.0NaN<p>Charting the last five tumultuous years, this final episode takes us to the end of 2020 and interrogates the methods used by celebrities to get everything they want.</p>NaNhttps://api.tvmaze.com/episodes/199407952661https://www.tvmaze.com/shows/52661/celebrity-a-21st-century-storyCelebrity: A 21st-Century StoryDocumentaryEnglish[History]To Be Determined60.060.02020-12-29Nonehttps://www.bbc.co.uk/programmes/m000qsk121:00[Tuesday]NaN27NaN26.0BBC iPlayerNaNhttps://www.bbc.co.uk/iplayerNaNNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/291/727584.jpghttps://static.tvmaze.com/uploads/images/original_untouched/291/727584.jpg<p>The world of celebrity has been transformed since the turn of the century, driven by some of the most dramatic technological and cultural developments in recent times.</p><p>This series charting the explosion in celebrity culture.</p>1611355220https://api.tvmaze.com/shows/52661https://api.tvmaze.com/episodes/1994079United KingdomGBEurope/Londonhttps://static.tvmaze.com/uploads/images/medium_landscape/291/727727.jpghttps://static.tvmaze.com/uploads/images/original_untouched/291/727727.jpgNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN